Data Engineer

Responsibilities

• Working with relevant business stake holder, explore, design and validate data products solutions including transformation and visualization to improve business productivity and new opportunities.

• Handling the requirement collection, translation and acceptance criteria formulation for data products including the schema design, storage methodologies and deployment model for data.

• Manage the overall operations, including the building, deploying, servicing as well as the on-going maintenance of data products related infrastructure that is part of project(s) scope.

• Provide support to other non-technical team members (or stakeholders) when related to data related expert inputs.

Skills Required

• At least 5 years of relevant experience in data analytics, data engineering and data validation in an enterprise environment with strong references over end-to-end data projects.

• Strong experience in BI visualization with Tableau is mandatory. Skills in Power BI will also be highly regarded.

• Experience and knowledge with Microsoft Fabric (inclusive of Fabric pipeline, Event House, semantic model) and Snowflake and other data platforms is highly regarded.

• Clear demonstration of capabilities in Python, SQL, Apache Flink, Apache Spark,ETL pipeline tools inclusive of Kettle, Azure DF, AWS Glue or similar tools.

• Clear demonstration of capabilities and experience in working with database systems such as Oracle, MS SQL Server, Postgres, MongoDB and MySQL. Experience with Neo4j, Qdrant, or Milvus will be highly regarded.

• Knowledge on common DevOps related tooling such as Git, Docker and related tools are essential. Candidates that can implement CI/CD over DataOps will be highly valued.