Job Scope:

• Commercial software engineering: Have strong professional software development experience in multiple programming languages, including modern virtual-machine languages such as Java, as well as common scripting and glue languages such as Python and version control (git), with good analytical & debugging skills.
• Experience performing root-cause analysis on bugs and performance problems in distributed systems, including network and source-level debugging
• Big data: You have extensive experience with data analytics and working knowledge of big data infrastructure such as Google Cloud, Big Query, Data Flow, Hadoop Eco System, HDFS, Apache Storm, Apache Spark
• You've routinely built data pipelines with gigabytes/terabytes of data and understand the challenges of manipulating such large datasets
• Cloud Exposure: Strong experience implementing systems and applications using distributed and cloud infrastructure. GCP preferred, but AWS or Azure are also okay
• Data Modeling: Flair for data, schema, data model, PL/SQL, Star & snowflake schema, how to bring efficiency in data modeling for efficient querying data for analysis, understands criticality TDD and develops data validation techniques
• Working knowledge of distributed relational and tabular data stores, message queues, stream processing facilities, and other scalable big-data platform technologies

Job Requirements:

• Responsible for integration and deployment of the Data Ingestion & machine learning pipelines into production where your ideas can come to life
• Work with stakeholders including the Data Science teams, Business Systems Analysts, and Architecture teams to assist with data platform technical and organizational issues and support the company's data and analytics needs
• Experience in designing and developing data warehouse workflows and big data development using Informatica PowerCenter or BDM
• Experience in working on Big Data Platform such as Cloudera/Hortonworks or Databricks or using Spark. • Experience in SQL using Oracle or MS SQL Server
• Good working knowledge in Big Data Technologies such as Hive, Hdfs
• Experience in data visualization development using Power BI, QlikView/QlikSense or Tableau

Job Scope:

• Responsible for integration and deployment of the Data Ingestion & machine learning pipelines into production where your ideas can come to life
• Work with stakeholders including the Data Science teams, Business Systems Analysts, and Architecture teams to assist with data platform technical and organizational issues and support the company's data and analytics needs

Job Requirements:

• Must have at least 2 years of relevant working experience in the following areas:
• Experience in designing and developing data warehouse workflows and big data development using Informatica PowerCenter or BDM
• Experience in working on Big Data Platform such as Cloudera/Hortonworks or Databricks or using Spark.
• Experience in SQL using Oracle or MS SQL Server
• Good working knowledge in Big Data Technologies such as Hive, Hdfs
• Good troubleshooting and problem-solving skills 4.4 Preferred skill sets:
• Experience in data visualization development using Power BI, QlikView/QlikSense or Tableau. Experience in scripts development in Unix or Linux environment.
• Able to work independently, with initiative and minimal guidance/supervision

Job Scope:

• Responsible for integration and deployment of the Data Ingestion & machine learning pipelines into production where your ideas can come to life
• Work with stakeholders including the Data Science teams, Business Systems Analysts, and Architecture teams to assist with data platform technical and organizational issues and support the company's data and analytics needs

Job Requirements:

• Must have at least 2 years of relevant working experience in the following areas:
• Experience in designing and developing data warehouse workflows and big data development using Informatica PowerCenter or BDM
• Experience in working on Big Data Platform such as Cloudera/Hortonworks or Databricks or using Spark.
• Experience in SQL using Oracle or MS SQL Server
• Good working knowledge in Big Data Technologies such as Hive, Hdfs
• Good troubleshooting and problem-solving skills 4.4 Preferred skill sets:
• Experience in data visualization development using Power BI, QlikView/QlikSense or Tableau. Experience in scripts development in Unix or Linux environment.

Able to work independently, with initiative and minimal guidance/supervision

Job Scope:

• Commercial software engineering: Have strong professional software development experience in multiple programming languages, including modern virtual-machine languages such as Java, as well as common scripting and glue languages such as Python and version control (git), with good analytical & debugging skills.
• Experience performing root-cause analysis on bugs and performance problems in distributed systems, including network and source-level debugging
• Big data: You have extensive experience with data analytics and working knowledge of big data infrastructure such as Google Cloud, Big Query, Data Flow, Hadoop Eco System, HDFS, Apache Storm, Apache Spark
• You've routinely built data pipelines with gigabytes/terabytes of data and understand the challenges of manipulating such large datasets
• Cloud Exposure: Strong experience implementing systems and applications using distributed and cloud infrastructure. GCP preferred, but AWS or Azure are also okay
• Data Modeling: Flair for data, schema, data model, PL/SQL, Star & snowflake schema, how to bring efficiency in data modeling for efficient querying data for analysis, understands criticality TDD and develops data validation techniques
• Working knowledge of distributed relational and tabular data stores, message queues, stream processing facilities, and other scalable big-data platform technologies

Job Requirements:

• Responsible for integration and deployment of the Data Ingestion & machine learning pipelines into production where your ideas can come to life
• Work with stakeholders including the Data Science teams, Business Systems Analysts, and Architecture teams to assist with data platform technical and organizational issues and support the company's data and analytics needs
• Experience in designing and developing data warehouse workflows and big data development using Informatica PowerCenter or BDM
• Experience in working on Big Data Platform such as Cloudera/Hortonworks or Databricks or using Spark. • Experience in SQL using Oracle or MS SQL Server
• Good working knowledge in Big Data Technologies such as Hive, Hdfs
• Experience in data visualization development using Power BI, QlikView/QlikSense or Tableau

• Product: Commercial Printers
• Basic $3000 - $3500
• Transport + Mobile Allowance ($440 - $840)
• AWS + Commission + Quarterly Bonus
• Gross up $4000++ monthly
• 5 days (8.30am - 5.30pm)
• Location: Jurong East

Responsibilities:

• Manage sales pipeline, monthly sales forecast and identify new business opportunities.
• Provide resources & support on product knowledge & sales strategies.
• Provide machine demo whenever required.
• Process sales related documentations – PO, contracts, sales requisition, credit grading, new customer code creation, transfer ownership.

Requirements:

• Min Diploma/ Degree in any field.
• Entry Level role, no experience required.
• On-Job training provided.
• Bilingual in Mandarin and English to liaise with Mandarin speaking clients.

For consideration, kindly submit your CV by clicking “APPLY Now”

**Only shortlisted candidate would be notified**

EA Reg. No: R23116143

Job Scope:

• Commercial software engineering: Have strong professional software development experience in multiple programming languages, including modern virtual-machine languages such as Java, as well as common scripting and glue languages such as Python and version control (git), with good analytical & debugging skills.
• Experience performing root-cause analysis on bugs and performance problems in distributed systems, including network and source-level debugging
• Big data: You have extensive experience with data analytics and working knowledge of big data infrastructure such as Google Cloud, Big Query, Data Flow, Hadoop Eco System, HDFS, Apache Storm, Apache Spark
• You've routinely built data pipelines with gigabytes/terabytes of data and understand the challenges of manipulating such large datasets
• Cloud Exposure: Strong experience implementing systems and applications using distributed and cloud infrastructure. GCP preferred, but AWS or Azure are also okay
• Data Modeling: Flair for data, schema, data model, PL/SQL, Star & snowflake schema, how to bring efficiency in data modeling for efficient querying data for analysis, understands criticality TDD and develops data validation techniques
• Working knowledge of distributed relational and tabular data stores, message queues, stream processing facilities, and other scalable big-data platform technologies

Job Requirements:

• Responsible for integration and deployment of the Data Ingestion & machine learning pipelines into production where your ideas can come to life
• Work with stakeholders including the Data Science teams, Business Systems Analysts, and Architecture teams to assist with data platform technical and organizational issues and support the company's data and analytics needs
• Experience in designing and developing data warehouse workflows and big data development using Informatica PowerCenter or BDM
• Experience in working on Big Data Platform such as Cloudera/Hortonworks or Databricks or using Spark. • Experience in SQL using Oracle or MS SQL Server
• Good working knowledge in Big Data Technologies such as Hive, Hdfs
• Experience in data visualization development using Power BI, QlikView/QlikSense or Tableau

Job Info:

• Salary: Basic up to $2400 + AWS + VB
• Working Hour: Monday - Friday (8:30am - 6pm)
• Location: Changi Airport Cargo

Job Scope:

• Offer general administrative and clerical support to the Cost Data Admin Department
• Update cost data for air, sea, and land freight shipments using the KEF system
• Coordinate with stakeholders to resolve any discrepancies
• Scan documents as required
• Organize PDF invoices received via email and upload them into folders for robotic process automation (RPA) execution
• Perform any additional tasks as assigned

Please submit your updated resume by using the APPLY NOW BUTTON

By submitting your personal data and/or resume to us in connection with your job application, you will be deemed to have agreed and consented to us in collecting, using, retaining, and disclosing your personal data and/or resume to prospective employers for the purpose of the evaluating, processing and administration by company relating to this job application.

*We regret to inform you that only shortlisted candidates would be notified*

We wish you all the best in your career search.

You are welcome to visit our website at http://www.rkgroup.sg/

RK Recruitment Pte Ltd | EA License No.: 20C0280

Chou Jia Hooi | EA Personnel No.: R23115147

Job Scope:

• Commercial software engineering: Have strong professional software development experience in multiple programming languages, including modern virtual-machine languages such as Java, as well as common scripting and glue languages such as Python and version control (git), with good analytical & debugging skills.
• Experience performing root-cause analysis on bugs and performance problems in distributed systems, including network and source-level debugging
• Big data: You have extensive experience with data analytics and working knowledge of big data infrastructure such as Google Cloud, Big Query, Data Flow, Hadoop Eco System, HDFS, Apache Storm, Apache Spark
• You've routinely built data pipelines with gigabytes/terabytes of data and understand the challenges of manipulating such large datasets
• Cloud Exposure: Strong experience implementing systems and applications using distributed and cloud infrastructure. GCP preferred, but AWS or Azure are also okay
• Data Modeling: Flair for data, schema, data model, PL/SQL, Star & snowflake schema, how to bring efficiency in data modeling for efficient querying data for analysis, understands criticality TDD and develops data validation techniques
• Working knowledge of distributed relational and tabular data stores, message queues, stream processing facilities, and other scalable big-data platform technologies

Job Requirements:

• Responsible for integration and deployment of the Data Ingestion & machine learning pipelines into production where your ideas can come to life
• Work with stakeholders including the Data Science teams, Business Systems Analysts, and Architecture teams to assist with data platform technical and organizational issues and support the company's data and analytics needs
• Experience in designing and developing data warehouse workflows and big data development using Informatica PowerCenter or BDM
• Experience in working on Big Data Platform such as Cloudera/Hortonworks or Databricks or using Spark. • Experience in SQL using Oracle or MS SQL Server
• Good working knowledge in Big Data Technologies such as Hive, Hdfs
• Experience in data visualization development using Power BI, QlikView/QlikSense or Tableau

Job Scope:

• Commercial software engineering: Have strong professional software development experience in multiple programming languages, including modern virtual-machine languages such as Java, as well as common scripting and glue languages such as Python and version control (git), with good analytical & debugging skills.
• Experience performing root-cause analysis on bugs and performance problems in distributed systems, including network and source-level debugging
• Big data: You have extensive experience with data analytics and working knowledge of big data infrastructure such as Google Cloud, Big Query, Data Flow, Hadoop Eco System, HDFS, Apache Storm, Apache Spark
• You've routinely built data pipelines with gigabytes/terabytes of data and understand the challenges of manipulating such large datasets
• Cloud Exposure: Strong experience implementing systems and applications using distributed and cloud infrastructure. GCP preferred, but AWS or Azure are also okay
• Data Modeling: Flair for data, schema, data model, PL/SQL, Star & snowflake schema, how to bring efficiency in data modeling for efficient querying data for analysis, understands criticality TDD and develops data validation techniques
• Working knowledge of distributed relational and tabular data stores, message queues, stream processing facilities, and other scalable big-data platform technologies

Job Requirements:

• Responsible for integration and deployment of the Data Ingestion & machine learning pipelines into production where your ideas can come to life
• Work with stakeholders including the Data Science teams, Business Systems Analysts, and Architecture teams to assist with data platform technical and organizational issues and support the company's data and analytics needs
• Experience in designing and developing data warehouse workflows and big data development using Informatica PowerCenter or BDM
• Experience in working on Big Data Platform such as Cloudera/Hortonworks or Databricks or using Spark. • Experience in SQL using Oracle or MS SQL Server
• Good working knowledge in Big Data Technologies such as Hive, Hdfs
• Experience in data visualization development using Power BI, QlikView/QlikSense or Tableau

Job Scope:

• Commercial software engineering: Have strong professional software development experience in multiple programming languages, including modern virtual-machine languages such as Java, as well as common scripting and glue languages such as Python and version control (git), with good analytical & debugging skills.
• Experience performing root-cause analysis on bugs and performance problems in distributed systems, including network and source-level debugging
• Big data: You have extensive experience with data analytics and working knowledge of big data infrastructure such as Google Cloud, Big Query, Data Flow, Hadoop Eco System, HDFS, Apache Storm, Apache Spark
• You've routinely built data pipelines with gigabytes/terabytes of data and understand the challenges of manipulating such large datasets
• Cloud Exposure: Strong experience implementing systems and applications using distributed and cloud infrastructure. GCP preferred, but AWS or Azure are also okay
• Data Modeling: Flair for data, schema, data model, PL/SQL, Star & snowflake schema, how to bring efficiency in data modeling for efficient querying data for analysis, understands criticality TDD and develops data validation techniques
• Working knowledge of distributed relational and tabular data stores, message queues, stream processing facilities, and other scalable big-data platform technologies

Job Requirements:

• Responsible for integration and deployment of the Data Ingestion & machine learning pipelines into production where your ideas can come to life
• Work with stakeholders including the Data Science teams, Business Systems Analysts, and Architecture teams to assist with data platform technical and organizational issues and support the company's data and analytics needs
• Experience in designing and developing data warehouse workflows and big data development using Informatica PowerCenter or BDM
• Experience in working on Big Data Platform such as Cloudera/Hortonworks or Databricks or using Spark. • Experience in SQL using Oracle or MS SQL Server
• Good working knowledge in Big Data Technologies such as Hive, Hdfs
• Experience in data visualization development using Power BI, QlikView/QlikSense or Tableau

Job Scope:

• Commercial software engineering: Have strong professional software development experience in multiple programming languages, including modern virtual-machine languages such as Java, as well as common scripting and glue languages such as Python and version control (git), with good analytical & debugging skills.
• Experience performing root-cause analysis on bugs and performance problems in distributed systems, including network and source-level debugging
• Big data: You have extensive experience with data analytics and working knowledge of big data infrastructure such as Google Cloud, Big Query, Data Flow, Hadoop Eco System, HDFS, Apache Storm, Apache Spark
• You've routinely built data pipelines with gigabytes/terabytes of data and understand the challenges of manipulating such large datasets
• Cloud Exposure: Strong experience implementing systems and applications using distributed and cloud infrastructure. GCP preferred, but AWS or Azure are also okay
• Data Modeling: Flair for data, schema, data model, PL/SQL, Star & snowflake schema, how to bring efficiency in data modeling for efficient querying data for analysis, understands criticality TDD and develops data validation techniques
• Working knowledge of distributed relational and tabular data stores, message queues, stream processing facilities, and other scalable big-data platform technologies

Job Requirements:

• Responsible for integration and deployment of the Data Ingestion & machine learning pipelines into production where your ideas can come to life
• Work with stakeholders including the Data Science teams, Business Systems Analysts, and Architecture teams to assist with data platform technical and organizational issues and support the company's data and analytics needs
• Experience in designing and developing data warehouse workflows and big data development using Informatica PowerCenter or BDM
• Experience in working on Big Data Platform such as Cloudera/Hortonworks or Databricks or using Spark. • Experience in SQL using Oracle or MS SQL Server
• Good working knowledge in Big Data Technologies such as Hive, Hdfs
• Experience in data visualization development using Power BI, QlikView/QlikSense or Tableau

Job Scope:

• Responsible for integration and deployment of the Data Ingestion & machine learning pipelines into production where your ideas can come to life
• Work with stakeholders including the Data Science teams, Business Systems Analysts, and Architecture teams to assist with data platform technical and organizational issues and support the company's data and analytics needs

Job Requirements:

• Must have at least 2 years of relevant working experience in the following areas:
• Experience in designing and developing data warehouse workflows and big data development using Informatica PowerCenter or BDM
• Experience in working on Big Data Platform such as Cloudera/Hortonworks or Databricks or using Spark.
• Experience in SQL using Oracle or MS SQL Server
• Good working knowledge in Big Data Technologies such as Hive, Hdfs
• Good troubleshooting and problem-solving skills 4.4 Preferred skill sets:
• Experience in data visualization development using Power BI, QlikView/QlikSense or Tableau. Experience in scripts development in Unix or Linux environment.

Able to work independently, with initiative and minimal guidance/supervision

Job Scope:

• Commercial software engineering: Have strong professional software development experience in multiple programming languages, including modern virtual-machine languages such as Java, as well as common scripting and glue languages such as Python and version control (git), with good analytical & debugging skills.
• Experience performing root-cause analysis on bugs and performance problems in distributed systems, including network and source-level debugging
• Big data: You have extensive experience with data analytics and working knowledge of big data infrastructure such as Google Cloud, Big Query, Data Flow, Hadoop Eco System, HDFS, Apache Storm, Apache Spark
• You've routinely built data pipelines with gigabytes/terabytes of data and understand the challenges of manipulating such large datasets
• Cloud Exposure: Strong experience implementing systems and applications using distributed and cloud infrastructure. GCP preferred, but AWS or Azure are also okay
• Data Modeling: Flair for data, schema, data model, PL/SQL, Star & snowflake schema, how to bring efficiency in data modeling for efficient querying data for analysis, understands criticality TDD and develops data validation techniques
• Working knowledge of distributed relational and tabular data stores, message queues, stream processing facilities, and other scalable big-data platform technologies

Job Requirements:

• Responsible for integration and deployment of the Data Ingestion & machine learning pipelines into production where your ideas can come to life
• Work with stakeholders including the Data Science teams, Business Systems Analysts, and Architecture teams to assist with data platform technical and organizational issues and support the company's data and analytics needs
• Experience in designing and developing data warehouse workflows and big data development using Informatica PowerCenter or BDM
• Experience in working on Big Data Platform such as Cloudera/Hortonworks or Databricks or using Spark. • Experience in SQL using Oracle or MS SQL Server
• Good working knowledge in Big Data Technologies such as Hive, Hdfs
• Experience in data visualization development using Power BI, QlikView/QlikSense or Tableau

Job Scope:

• Responsible for integration and deployment of the Data Ingestion & machine learning pipelines into production where your ideas can come to life
• Work with stakeholders including the Data Science teams, Business Systems Analysts, and Architecture teams to assist with data platform technical and organizational issues and support the company's data and analytics needs

Job Requirements:

• Must have at least 2 years of relevant working experience in the following areas:
• Experience in designing and developing data warehouse workflows and big data development using Informatica PowerCenter or BDM
• Experience in working on Big Data Platform such as Cloudera/Hortonworks or Databricks or using Spark.
• Experience in SQL using Oracle or MS SQL Server
• Good working knowledge in Big Data Technologies such as Hive, Hdfs
• Good troubleshooting and problem-solving skills 4.4 Preferred skill sets:
• Experience in data visualization development using Power BI, QlikView/QlikSense or Tableau. Experience in scripts development in Unix or Linux environment.

Able to work independently, with initiative and minimal guidance/supervision

Job Scope:

• Commercial software engineering: Have strong professional software development experience in multiple programming languages, including modern virtual-machine languages such as Java, as well as common scripting and glue languages such as Python and version control (git), with good analytical & debugging skills.
• Experience performing root-cause analysis on bugs and performance problems in distributed systems, including network and source-level debugging
• Big data: You have extensive experience with data analytics and working knowledge of big data infrastructure such as Google Cloud, Big Query, Data Flow, Hadoop Eco System, HDFS, Apache Storm, Apache Spark
• You've routinely built data pipelines with gigabytes/terabytes of data and understand the challenges of manipulating such large datasets
• Cloud Exposure: Strong experience implementing systems and applications using distributed and cloud infrastructure. GCP preferred, but AWS or Azure are also okay
• Data Modeling: Flair for data, schema, data model, PL/SQL, Star & snowflake schema, how to bring efficiency in data modeling for efficient querying data for analysis, understands criticality TDD and develops data validation techniques
• Working knowledge of distributed relational and tabular data stores, message queues, stream processing facilities, and other scalable big-data platform technologies

Job Requirements:

• Responsible for integration and deployment of the Data Ingestion & machine learning pipelines into production where your ideas can come to life
• Work with stakeholders including the Data Science teams, Business Systems Analysts, and Architecture teams to assist with data platform technical and organizational issues and support the company's data and analytics needs
• Experience in designing and developing data warehouse workflows and big data development using Informatica PowerCenter or BDM
• Experience in working on Big Data Platform such as Cloudera/Hortonworks or Databricks or using Spark. • Experience in SQL using Oracle or MS SQL Server
• Good working knowledge in Big Data Technologies such as Hive, Hdfs
• Experience in data visualization development using Power BI, QlikView/QlikSense or Tableau

Job Scope:

• Commercial software engineering: Have strong professional software development experience in multiple programming languages, including modern virtual-machine languages such as Java, as well as common scripting and glue languages such as Python and version control (git), with good analytical & debugging skills.
• Experience performing root-cause analysis on bugs and performance problems in distributed systems, including network and source-level debugging
• Big data: You have extensive experience with data analytics and working knowledge of big data infrastructure such as Google Cloud, Big Query, Data Flow, Hadoop Eco System, HDFS, Apache Storm, Apache Spark
• You've routinely built data pipelines with gigabytes/terabytes of data and understand the challenges of manipulating such large datasets
• Cloud Exposure: Strong experience implementing systems and applications using distributed and cloud infrastructure. GCP preferred, but AWS or Azure are also okay
• Data Modeling: Flair for data, schema, data model, PL/SQL, Star & snowflake schema, how to bring efficiency in data modeling for efficient querying data for analysis, understands criticality TDD and develops data validation techniques
• Working knowledge of distributed relational and tabular data stores, message queues, stream processing facilities, and other scalable big-data platform technologies

Job Requirements:

• Responsible for integration and deployment of the Data Ingestion & machine learning pipelines into production where your ideas can come to life
• Work with stakeholders including the Data Science teams, Business Systems Analysts, and Architecture teams to assist with data platform technical and organizational issues and support the company's data and analytics needs
• Experience in designing and developing data warehouse workflows and big data development using Informatica PowerCenter or BDM
• Experience in working on Big Data Platform such as Cloudera/Hortonworks or Databricks or using Spark. • Experience in SQL using Oracle or MS SQL Server
• Good working knowledge in Big Data Technologies such as Hive, Hdfs
• Experience in data visualization development using Power BI, QlikView/QlikSense or Tableau

Job Scope:

• Commercial software engineering: Have strong professional software development experience in multiple programming languages, including modern virtual-machine languages such as Java, as well as common scripting and glue languages such as Python and version control (git), with good analytical & debugging skills.
• Experience performing root-cause analysis on bugs and performance problems in distributed systems, including network and source-level debugging
• Big data: You have extensive experience with data analytics and working knowledge of big data infrastructure such as Google Cloud, Big Query, Data Flow, Hadoop Eco System, HDFS, Apache Storm, Apache Spark
• You've routinely built data pipelines with gigabytes/terabytes of data and understand the challenges of manipulating such large datasets
• Cloud Exposure: Strong experience implementing systems and applications using distributed and cloud infrastructure. GCP preferred, but AWS or Azure are also okay
• Data Modeling: Flair for data, schema, data model, PL/SQL, Star & snowflake schema, how to bring efficiency in data modeling for efficient querying data for analysis, understands criticality TDD and develops data validation techniques
• Working knowledge of distributed relational and tabular data stores, message queues, stream processing facilities, and other scalable big-data platform technologies

Job Requirements:

• Responsible for integration and deployment of the Data Ingestion & machine learning pipelines into production where your ideas can come to life
• Work with stakeholders including the Data Science teams, Business Systems Analysts, and Architecture teams to assist with data platform technical and organizational issues and support the company's data and analytics needs
• Experience in designing and developing data warehouse workflows and big data development using Informatica PowerCenter or BDM
• Experience in working on Big Data Platform such as Cloudera/Hortonworks or Databricks or using Spark. • Experience in SQL using Oracle or MS SQL Server
• Good working knowledge in Big Data Technologies such as Hive, Hdfs
• Experience in data visualization development using Power BI, QlikView/QlikSense or Tableau

Job Scope:

• Commercial software engineering: Have strong professional software development experience in multiple programming languages, including modern virtual-machine languages such as Java, as well as common scripting and glue languages such as Python and version control (git), with good analytical & debugging skills.
• Experience performing root-cause analysis on bugs and performance problems in distributed systems, including network and source-level debugging
• Big data: You have extensive experience with data analytics and working knowledge of big data infrastructure such as Google Cloud, Big Query, Data Flow, Hadoop Eco System, HDFS, Apache Storm, Apache Spark
• You've routinely built data pipelines with gigabytes/terabytes of data and understand the challenges of manipulating such large datasets
• Cloud Exposure: Strong experience implementing systems and applications using distributed and cloud infrastructure. GCP preferred, but AWS or Azure are also okay
• Data Modeling: Flair for data, schema, data model, PL/SQL, Star & snowflake schema, how to bring efficiency in data modeling for efficient querying data for analysis, understands criticality TDD and develops data validation techniques
• Working knowledge of distributed relational and tabular data stores, message queues, stream processing facilities, and other scalable big-data platform technologies

Job Requirements:

• Responsible for integration and deployment of the Data Ingestion & machine learning pipelines into production where your ideas can come to life
• Work with stakeholders including the Data Science teams, Business Systems Analysts, and Architecture teams to assist with data platform technical and organizational issues and support the company's data and analytics needs
• Experience in designing and developing data warehouse workflows and big data development using Informatica PowerCenter or BDM
• Experience in working on Big Data Platform such as Cloudera/Hortonworks or Databricks or using Spark. • Experience in SQL using Oracle or MS SQL Server
• Good working knowledge in Big Data Technologies such as Hive, Hdfs
• Experience in data visualization development using Power BI, QlikView/QlikSense or Tableau

Job Scope:

• Responsible for integration and deployment of the Data Ingestion & machine learning pipelines into production where your ideas can come to life
• Work with stakeholders including the Data Science teams, Business Systems Analysts, and Architecture teams to assist with data platform technical and organizational issues and support the company's data and analytics needs

Job Requirements:

• Must have at least 2 years of relevant working experience in the following areas:
• Experience in designing and developing data warehouse workflows and big data development using Informatica PowerCenter or BDM
• Experience in working on Big Data Platform such as Cloudera/Hortonworks or Databricks or using Spark.
• Experience in SQL using Oracle or MS SQL Server
• Good working knowledge in Big Data Technologies such as Hive, Hdfs
• Good troubleshooting and problem-solving skills 4.4 Preferred skill sets:
• Experience in data visualization development using Power BI, QlikView/QlikSense or Tableau. Experience in scripts development in Unix or Linux environment.

Able to work independently, with initiative and minimal guidance/supervision

Job Scope:

• Responsible for integration and deployment of the Data Ingestion & machine learning pipelines into production where your ideas can come to life
• Work with stakeholders including the Data Science teams, Business Systems Analysts, and Architecture teams to assist with data platform technical and organizational issues and support the company's data and analytics needs

Job Requirements:

• Must have at least 2 years of relevant working experience in the following areas:
• Experience in designing and developing data warehouse workflows and big data development using Informatica PowerCenter or BDM
• Experience in working on Big Data Platform such as Cloudera/Hortonworks or Databricks or using Spark.
• Experience in SQL using Oracle or MS SQL Server
• Good working knowledge in Big Data Technologies such as Hive, Hdfs
• Good troubleshooting and problem-solving skills 4.4 Preferred skill sets:
• Experience in data visualization development using Power BI, QlikView/QlikSense or Tableau. Experience in scripts development in Unix or Linux environment.
• Able to work independently, with initiative and minimal guidance/supervision

Mandatory Skills

Responsibilities:

1. Utilize extensive financial datasets to drive the bank's Treasury and Market department's data science solutions for pricing, campaign optimization, and customer hyper-personalization.
2. Work with quants, traders and dealers to solve complex optimization problems using advanced machine learning and quantitative methods.
3. Develop causal models and optimization algorithms to dynamically price financial products and respond to market volatility.
4. Strategize, execute, and evaluate marketing campaigns and pricing experiments.
5. Conduct research and literature reviews to assess quantitative algorithms and models, ensuring the selection of optimal methodologies.
6. Perform hypothesis testing to discover causal drivers for customer and market behaviours.
7. Implement and train AI/ML models, optimizing algorithm efficiency through GPU distributed computing and concurrent programming.
8. Write and refactor code into reusable libraries/ APIs, deploy machine learning ecosystems, and integrate subsystems as necessary.

Required Experience:

• Masters/ PhD in a quantitative discipline, such as Mathematics/Statistics, Quantitative Finance, Computer Science, Engineering, or equivalent experience.
• Proficient in the data science production life cycle, with a track record of working with structured, semi-structured, and unstructured data.
• Exceptional software skills in Python (Or demonstrable ability to pick up new languages) and SQL variants, with expertise in design patterns, code optimization, and object-oriented programming.
• Experience applying quantitative and machine learning algorithms to pricing and marketing domains.
• Demonstrable expertise in econometrics, statistical modelling, time-series analysis, causal inference, or other relevant domains.
• Solid understanding of foreign exchange markets, including currency pairs, market dynamics, and key drivers.
• Hands-on experience in designing and executing digital campaigns and experimentation methodologies, including A/B testing, bandit-based experiments and multivariate analysis.

Key Skills:

Python, machine learning, causal inference, SQL, experimentation, A/B Testing, Multi-Armed bandit, pricing, econometrics, software design, time-series analysis, research, financial markets, behavioral science, quantitative analysis.

Mandatory Skills

Responsibilities:

1. Utilize extensive financial datasets to drive the bank's Treasury and Market department's data science solutions for pricing, campaign optimization, and customer hyper-personalization.
2. Work with quants, traders and dealers to solve complex optimization problems using advanced machine learning and quantitative methods.
3. Develop causal models and optimization algorithms to dynamically price financial products and respond to market volatility.
4. Strategize, execute, and evaluate marketing campaigns and pricing experiments.
5. Conduct research and literature reviews to assess quantitative algorithms and models, ensuring the selection of optimal methodologies.
6. Perform hypothesis testing to discover causal drivers for customer and market behaviours.
7. Implement and train AI/ML models, optimizing algorithm efficiency through GPU distributed computing and concurrent programming.
8. Write and refactor code into reusable libraries/ APIs, deploy machine learning ecosystems, and integrate subsystems as necessary.

Required Experience:

• Masters/ PhD in a quantitative discipline, such as Mathematics/Statistics, Quantitative Finance, Computer Science, Engineering, or equivalent experience.
• Proficient in the data science production life cycle, with a track record of working with structured, semi-structured, and unstructured data.
• Exceptional software skills in Python (Or demonstrable ability to pick up new languages) and SQL variants, with expertise in design patterns, code optimization, and object-oriented programming.
• Experience applying quantitative and machine learning algorithms to pricing and marketing domains.
• Demonstrable expertise in econometrics, statistical modelling, time-series analysis, causal inference, or other relevant domains.
• Solid understanding of foreign exchange markets, including currency pairs, market dynamics, and key drivers.
• Hands-on experience in designing and executing digital campaigns and experimentation methodologies, including A/B testing, bandit-based experiments and multivariate analysis.

Key Skills:

Python, machine learning, causal inference, SQL, experimentation, A/B Testing, Multi-Armed bandit, pricing, econometrics, software design, time-series analysis, research, financial markets, behavioral science, quantitative analysis.

Mandatory Skills

Responsibilities:

1. Utilize extensive financial datasets to drive the bank's Treasury and Market department's data science solutions for pricing, campaign optimization, and customer hyper-personalization.
2. Work with quants, traders and dealers to solve complex optimization problems using advanced machine learning and quantitative methods.
3. Develop causal models and optimization algorithms to dynamically price financial products and respond to market volatility.
4. Strategize, execute, and evaluate marketing campaigns and pricing experiments.
5. Conduct research and literature reviews to assess quantitative algorithms and models, ensuring the selection of optimal methodologies.
6. Perform hypothesis testing to discover causal drivers for customer and market behaviours.
7. Implement and train AI/ML models, optimizing algorithm efficiency through GPU distributed computing and concurrent programming.
8. Write and refactor code into reusable libraries/ APIs, deploy machine learning ecosystems, and integrate subsystems as necessary.

Required Experience:

• Masters/ PhD in a quantitative discipline, such as Mathematics/Statistics, Quantitative Finance, Computer Science, Engineering, or equivalent experience.
• Proficient in the data science production life cycle, with a track record of working with structured, semi-structured, and unstructured data.
• Exceptional software skills in Python (Or demonstrable ability to pick up new languages) and SQL variants, with expertise in design patterns, code optimization, and object-oriented programming.
• Experience applying quantitative and machine learning algorithms to pricing and marketing domains.
• Demonstrable expertise in econometrics, statistical modelling, time-series analysis, causal inference, or other relevant domains.
• Solid understanding of foreign exchange markets, including currency pairs, market dynamics, and key drivers.
• Hands-on experience in designing and executing digital campaigns and experimentation methodologies, including A/B testing, bandit-based experiments and multivariate analysis.

Key Skills:

Python, machine learning, causal inference, SQL, experimentation, A/B Testing, Multi-Armed bandit, pricing, econometrics, software design, time-series analysis, research, financial markets, behavioral science, quantitative analysis.

Mandatory Skills

• CAT-1 cleared/eligible candidate is required for this role.
• Experience in data analysis.
• Experience in managing data reconciliation/quality checks (implementation, monitoring and troubleshooting).
• Hands-on experience with Oracle PL/SQL.
• Experience in performing UAT.
• Able to manage SLA and queries from end users.
• Experience in providing documentation support, e.g. in technical/functional specifications.
• Possess finance domain knowledge.
• Good problem solving and logical thinking.

Skillsets (Good to have)

• Snowflake
• Denodo

Brief Job Description

Summary:

supporting data management operations activities for U2ID and TPDM applications.

Mandatory Skills

• CAT-1 cleared/eligible candidate is required for this role.
• Experience in data analysis.
• Experience in managing data reconciliation/quality checks (implementation, monitoring and troubleshooting).
• Hands-on experience with Oracle PL/SQL.
• Experience in performing UAT.
• Able to manage SLA and queries from end users.
• Experience in providing documentation support, e.g. in technical/functional specifications.
• Possess finance domain knowledge.
• Good problem solving and logical thinking.

Skillsets (Good to have)

• Snowflake
• Denodo