The Data Engineer manages his/her position by creating data models optimized for performance, implementing schema changes, and maintaining
data architecture standards across all the business databases. This position is additionally tasked with designing and developing scalable ETL packages using Microsoft SQL Server Integration Services (SSIS), and the development of ETL routines to populate databases from sources and create aggregates. Data Engineer leads innovation through exploration, benchmarking, making recommendations, and implementing data technologies.
Tasks and Requirements:
- Responsible for performing thorough testing and validation to support the accuracy of data transformations and data verification.
- The position strives to ensure proper data governance and quality across the Data and Analytics organization and the business as a whole.
- The Data Engineer plays a support analytics role where he/she performs ad-hoc analysis of data stored in source and Data Warehouse databases. Further, he/she writes SQL Scripts, stored procedures, functions, and views.
- This position supports to the need to troubleshoot data issues and present solutions to these issues. He/she analyzes and evaluates the databases to identify and recommend improvements and optimization.
- Data Engineer prepares activity and progress reports regarding the database status and health, which are presented to the team for future activities to proactively prevent data corruption, data failure, etc.
- The Data Engineer will additionally analyze complex data elements and systems, data flow, dependencies, and relationships to contribute to
conceptual physical and logical data models.
- Creates reports using Microsoft SQL Server Reporting Services (SSRS); writes complex SQL queries against SQL server database to validate the reports and provide performance tuning and maintenance of existing reports.
- Maintains up-to-date documentation, including diagrams, on all BI/applications development, database systems, integration services and connectivity.
- Excellent understanding of OLTP and OLAP systems is a must.
- Designs and Implements cloud data platforms and cloud-related architectures.
- Supports in Snowflake design patterns and migration architectures a major plus.
- Support in migration, dev/ops, ETL/ELT, and BI is required.
- Knowledge of python and Snowflake is a HUGE advantage