Total 8 data entry job vacancies in Information Technology category in D27 Yishun, Sembawang

Job Description: Azure Data Engineer

We are seeking a skilled Azure Data Engineer with a minimum of 2 years of hands-on experience in Azure data services. The ideal candidate will play a critical role in designing, developing, and optimizing data pipelines and analytics solutions to support our organization’s data-driven initiatives.

Key Responsibilities:

• Design, develop, and maintain data pipelines using Azure Data Factory.
• Implement and manage data integration and transformation workflows.
• Build, optimize, and maintain scalable data solutions using Azure Synapse Analytics or Azure Datawarehouse.
• Collaborate with cross-functional teams to gather requirements and deliver data solutions aligned with business objectives.
• Ensure data quality, consistency, and reliability across all data processes.
• Monitor, troubleshoot, and improve data workflows for performance and scalability.
• Stay updated on industry best practices and emerging Azure technologies to implement innovative solutions.

Requirements:

• Experience: At least 2 years of hands-on experience with Azure Data Factory and Azure Synapse Analytics/Datawarehouse.
• Certifications: Preferably holds a Microsoft Azure Data Engineer Associate certification or other relevant Microsoft certifications.
• Strong understanding of data integration, ETL/ELT processes, and data modeling.
• Familiarity with Azure cloud ecosystem and services (e.g., Azure Storage, Azure SQL Database).
• Solid experience with SQL for querying and managing data.
• Strong problem-solving skills and the ability to work independently or in a team environment.
• Excellent communication and interpersonal skills for effective collaboration with technical and non-technical stakeholders.

Preferred Qualifications:

• Experience with data governance, security, and compliance in cloud environments.
• Knowledge of scripting languages (e.g., Python, PowerShell) for automation.
• Familiarity with big data tools and frameworks within Azure.

Responsibilities include, but not limited to:

• Strong desire to grow a career as a Data Scientist in highly automated industrial manufacturing doing analysis and machine learning on terabytes and petabytes of diverse datasets.
• Experience in the areas: statistical modeling, feature extraction and analysis, supervised/unsupervised/semi-supervised learning. Exposure to the semiconductor industry is a plus but not a requirement.
• Ability to extract data from different databases via SQL and other query languages and applying data cleansing, outlier identification, and missing data techniques.
• Strong software development skills.
• Strong verbal and written communication skills.
• Experience with or desire to learn:
• Machine learning and other advanced analytical methods
• Fluency in Python and/or R
• pySpark and/or SparkR and/or SparklyR
• Hadoop (Hive, Spark, HBase)
• Teradata and/or another SQL databases
• Tensorflow, and/or other statistical software including scripting capability for automating analyses
• SSIS, ETL
• Javascript, AngularJS 2.0, Tableau
• Experience working with time-series data, images, semi-supervised learning, and data with frequently changing distributions is a plus
• Experience working with Manufacturing Execution Systems (MES) is a plus
• Existing papers from CVPR, NIPS, ICML, KDD, and other key conferences are plus, but this is not a research position

Designs, develops and programs methods, processes, and systems to consolidate and analyze unstructured, diverse “big data” sources to generate actionable insights and solutions for client services and product enhancement. Interacts with product and service teams to identify questions and issues for data analysis and experiments. Develops and codes software programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources. Identifies meaningful insights from large data and metadata sources; interprets and communicates insights and findings from analysis and experiments to product, service, and business managers.

Key Responsibilities

• Analyse the Authority’s data needs and document the requirements.

• Refine data collection/consumption by migrating data collection to more efficient channels.

• Plan, design and implement data engineering jobs and reporting solutions to meet the analytical needs.

• Develop test plan and scripts for system testing, support user acceptance testing.

• Work with the Authority’s technical teams to ensure smooth deployment and adoption of new solution.

• Ensure the smooth operations and service level of IT solutions.

• Support production issues.

What we are looking for

• Good understanding and completion of projects using waterfall/Agile methodology.

• Hands-on experience in DevOps deployment and data virtualisation tools like Denodo will be preferred.

• Understanding of reporting or visualization tool like SAP BO and Tableau is important.

• Track record in implementing systems using Hive, Impala and Cloudera Data Platform will be preferred.

• Hands-on experience in big data engineering jobs using Python, Pyspark, Linux, and ETL tools like Informatica.

• Strong SQL and data modelling and data analysis skills.

• Good understanding of analytics and data warehouse implementations.

• Ability to troubleshoot complex issues ranging from system resource to application stack traces.

• Track record in implementing systems with high availability, high performance, high security hosted at various data centres or hybrid cloud environments will be an added advantage

Job Description

1 .Collect, clean, and analyse key data from the Finance including removing duplicates, standardizing formats, and updating outdated or inaccurate information

2. Perform checks to verify accuracy and completeness by cross-referencing with reliable sources

3. Identify and fix inconsistencies to maintain data integrity

4. Ensure data quality and accuracy by managing the cleansing process for Finance .

5. Support Oracle NetSuite migration by ensuring accurate and timely data entry and validation

6. Compile large datasets efficiently for future reporting and analysis

7. Provide support to the daily operations of the Finance as needed.

8. Any other ad-hoc duties as assigned

Education Required:
▪Diploma or Degree in Supply Chain Management, or a related field
Experience Required:

▪ Intern can Apply
▪ At least 2 years of experience in data cleansing and migration within an ERP environment
Competencies and Skills Required
▪ Proficient in Microsoft Excel
▪ Knowledge of ERP systems, experience with Oracle NetSuite is a strong advantage
▪ Strong attention to details and organizational skills
▪ Ability to work independently and collaboratively within a team

Keysight is on the forefront of technology innovation, delivering breakthroughs and trusted insights in electronic design, simulation, prototyping, test, manufacturing, and optimization. Our ~15,000 employees create world-class solutions in communications, 5G, automotive, energy, quantum, aerospace, defense, and semiconductor markets for customers in over 100 countries. Learn more about what we do.

Our powerful, award-winning culture embraces a bold vision of where technology can take us and a passion for tackling challenging problems with industry-first solutions. Diversity, equity & inclusion are integral parts of our culture and drivers of innovation at Keysight. We believe that when people feel a sense of belonging, they can be more creative, innovative, and thrive at all points in their careers.

Job Description

This position is for a full-time Software Engineer to join Keysight’s Quantum Engineering Solutions (QES) organization, which is responsible for producing world-leading solutions in quantum technologies, including quantum computing, quantum communications and quantum sensing. As a Solution Developer, you will be part of an R&D team and launch breakthrough software solutions to market. You will engage in every stage of our product development process, addressing intricate technical hurdles in a customer-centric setting, while implementing a novel method for integrating classical data systems with quantum operations and third-party software as a Data Engineer.

Job Responsibilities

• Architect and implement scalable, cutting-edge data workflows to support quantum computing operations, including experiment data processing, calibration, and real-time analytics.
• Leverage advanced automation tools to manage and orchestrate workflows that integrate data from classical systems into quantum environments, ensuring high reliability and efficiency.
• Build and maintain data infrastructure, ensuring proper version control, data lineage, and efficient handling of large datasets produced by quantum experiments.
• Continuously analyze and optimize data workflows to enhance throughput, reduce latency, and improve overall system performance in a research-driven environment.
• Work independently as well as in teams to accomplish business objectives.

Job Qualifications

• Bachelor’s, Master’s, or PhD in Computer Science, Physics, Electrical Engineering, or a related field with 4-7 years job experience.
• Good understanding of quantum computing concepts, and experience integrating classical data workflows with quantum experiments is highly desirable.
• Background in High-Performance Computing (HPC), data-intensive research projects, or scientific computing environments is preferred.
• Expertise in Python for developing, automating, and optimizing scientific data processing systems.
• Experience designing and managing data workflows using tools like Airflow, Spark, or similar, with a strong understanding of ETL processes and data infrastructure.
• Strong experience in SQL for querying, transforming, and managing large datasets.
• Knowledge of optimization techniques and algorithms.
• Ability to work in a collaborative environment and to develop teamwork among individuals and over geographically disperse teams.
• High tolerance for ambiguity, results-oriented, meets timelines, handles pressure while working positively in a collaborative manner.
• Excellent written and verbal communication skills
• Willingness to learn proactively.

About the job Reporting and Analytics Developer/Data Engineer

We are seeking a highly skilled and experienced Big Data Engineer to join our team. The ideal candidate must have a minimum of 4 years of experience managing data engineering jobs in big data environment e.g., Cloudera Data Platform. Overall experience can be 4 to 10 years. Consultant/ Senior Consultant preferably. The successful candidate will be responsible for designing, developing, and maintaining the data ingestion and processing jobs as per business requirements. Candidate will also be integrating data sets to provide seamless data access to users.

Key Responsibilities:

• Analyze the Authoritys data needs and document the requirements.
• Refine data collection/consumption by migrating data collection to more efficient channels.
• Plan, design and implement data engineering jobs and reporting solutions to meet the analytical needs.
• Develop test plan and scripts for system testing, support user acceptance testing.
• Work with the Authoritys technical teams to ensure smooth deployment and adoption of new solution.
• Ensure the smooth operations and service level of IT solutions.
• Support production issues - Track record in implementing systems with high availability, high performance, high security.

What are we looking for:

• Good understanding and completion of projects using waterfall/Agile methodology.
• Good understanding of analytics and data warehouse implementations.
• Ability to troubleshoot complex issues ranging from system resource to application stack traces.
• Strong SQL, data modelling and data analysis skills are a must.
• Hands-on experience in big data engineering jobs using Python, PySpark, Linux, and ETL tools like Informatica.
• Track record in implementing systems using Hive, Impala and Cloudera Data Platform will be preferred.
• Hands-on experience in DevOps deployment and data virtualization tools like Denodo will be preferred.
• Understanding/ Hands on experience of reporting or visualization tool like SAP BO and Tableau will be beneficial but not required.
• Passion for automation, standardization, and best practices.
• Good written and verbal communication and interpersonal skills, ability to understand the business requirement, communicate confidently with stakeholders.

• Strong desire to grow a career as a Data Scientist in highly automated industrial manufacturing doing analysis and machine learning on terabytes and petabytes of diverse datasets.
• Experience in the areas: statistical modeling, feature extraction and analysis, supervised/unsupervised/semi-supervisedlearning. Exposure to the semiconductor industry is a plus but not a requirement.
• Ability to extract data from different databases via SQL and other query languages and applying data cleansing, outlier identification, and missing data techniques.
• Strong software development skills.
• Strong verbal and written communication skills.
• Experience with or desire to learn:
• Machine learning and other advanced analytical methods
• Fluency in Python and/or R
• pySpark and/or SparkR and/or SparklyR
• Hadoop (Hive, Spark, HBase)
• Teradata and/or another SQL databases
• Tensorflow, and/or other statistical software including scripting capability for automating analyses
• SSIS, ETL
• Javascript, AngularJS 2.0, Tableau
• Experience working with time-series data, images, semi-supervised learning, and data with frequently changing distributions is a plus
• Experience working with Manufacturing Execution Systems (MES) is a plus
• Existing papers from CVPR, NIPS, ICML, KDD, and other key conferences are plus, but this is not a research position

Required Skills

· Build, deploy and manage Data security products to secure and implement governance policies on the data assets in the organization.

· Integrate security frameworks on modern high-performance analytics database and computation engines like Spark, Presto, Kafka, Elastic, and technologies in the stack

· Java - SpringBoot

· NoSQL Databases

· Distributed computing

· Data & API Integration

· Networking

· AWS/GCP/Azure

· Identity and Access Management (IAM)

· Docker/Kubernetes/OpenShift