Job Summary
A great opportunity as a Data Engineer to work in cloud based data engineering, analytics and data management team in a well established company.
Mandatory Skill-set
- Bachelor's Degree in Computer Science or equivalent;
- Minimum 5 years of experience in data engineering and data management;
- Hands on technical experience in Azure Data Factory, Databricks, Synapse, SQL Server Integration Services;
- Strong experience in Python / SAS / R along with Tableau / Power BI;
- Strong experience in gathering business requirements and translating into technical specification;
- Strong analytical skills with high curiosity to deep dive into root cause of problems and suggest solutions;
- Has good stakeholders management experience;
- Attention to technical details;
- Ability to deliver tasks on time with high quality outcome;
- Self motivated and ability to take ownership;
- Strong written and spoken communication skills.
Desired Skill-set
- Azure Data Engineer Certified;
- ITIL certified;
- Prior experience in Python, R or Machine Learning tools.
Responsibilities
- Design and develop data models, ETL pipelines, data integration process while ensuring data accuracy and quality;
- Perform data analysis of structured and unstructured data and perform business intelligence initiatives such as build user friendly reports using data visualization tools;
- Analyze ETL requirements from users and provide solutions accordingly;
- Responsible for planning and executing data profiling and data quality analysis;
- Monitor data pipelines, databases and analytical processes to ensure smooth operations;
- Identify and resolve data-related issues, performance bottleneck and data quality problems;
- Design and document data catalogs and data architectures;
- Perform regular data cleansing exercise to ensure that data is of high quality and relevant to the business needs;
- Execute data transformation, correction and aggregations to ensure compliance with business / regulatory requests;
- Build and maintain reports and dashboards using suitable data visualization tools;
- Conduct analysis on the reports and translate the findings into valuable insights to business users;
- Prepare data for prescriptive and predictive modelling;
- Perform database monitoring and performance tuning.
