Data Engineer

The data engineer plays a key role in the development of data ingestion, data integration and analytics solutions (data warehouses, data marts)

The data engineer sits within the central Data Office which is a central organization providing data services across the different NIHDI business lines. He/she works in an agile scrum team in close collaboration with the Project Leader, the Data Functional Analyst and the Data Architect of the project.

Roles & Responsibilities

· Translate business, functional and data architectural requirements provided by the Data Functional Analyst and the Data Architect into technical specifications.

· Design, build, deploy and maintain data solutions (ETL pipeline, database objects, physical and virtual datamarts) according to established standards (data processing, data warehouse, data marts) in accordance with the functional and non-functional requirements (performance, data volume).

· Test the analytics solution, ensure the data correctness, conduct troubleshooting, provide maintenance and adequate technical documentation.

· Works with the Project Leader (PL) along the entire project lifecycle to ensure appropriate delivery in an agile and pragmatic approach.

· Integrate referential data into a central data hub.

Key Skills

· Bachelor or Master degree in Computer Science or equivalent

· Experience as a data engineer in the Microsoft BI on-prem stack (Visual Studio, SSIS, SSAS, SSMS)

· Experience as a data engineer with Azure databricks.

· Ability to translate business requirements into technical requirements

· Data modelling experience (logical and physical modelling)

· Good experience in data warehouse design (Kimball dimensional modelling)

· Very good knowledge of Microsoft SQL Server (from a development perspective) and Delta Lake.

· Very good Knowledge of SQL queries, T-SQL, SQL Server Integration Services (SSIS).

· Very good Knowledge of Python (from a data engineer perspective), pandas and Apache Spark.

· Very good understanding of database management systems, online analytical processing (OLAP) and ETL (Extract, transform, load) framework

· Experience in master and reference data integration and usage

· Experience in working in an agile project mode.

· Experience in building a data validation engine (business rules, semantic validation) is a plus

· Experience in visualization tool such as Microsoft Power BI and SSRS is a plus.

· Experience in data functional analysis is a plus.

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