Job Location: Gurgaon/Gurugram
– Work alongside the central data quality team and data engineers to ensure high quality data and observability
– Work with SMEs and data stewards to help identify inconsistencies in data, and how they are manifested from source and integration processes
– Utilize data quality assurance frameworks to support the process of identifying inconsistencies across data
– Develop test data scripts (primarily in SQL & Python) based on ETL mapping artifacts and other technical documentation
– Integration testing – Services, ETL, Database (SQLOracle) – covering DML Validations, Batch Monitoring etc
– Track, monitor, and document testing results within the data quality assurance framework and COTS software
– Be responsible for data profiling and coordinating with data stewards to extract meaningful requirements
– Work with Data Engineers to implement process logic that will act on the findings of data quality assessments
Must have :
– Bachelor’s degree in a related field such as Computer Science, Information Systems, Data Engineering, Applied Math, etc.
– 3+ years of data engineering analytics working experience
– Expert-level experience with SQL across a variety of platforms, writing complex queries
– Proficient in Python coding and data analysis via Jupyter Notebooks
– Experience working with Data WarehousesData Marts as well as Data Lakes, and data in a variety of volumes and formats
– Experience with configuring and maintaining a data quality and management tools
– Knowledge of database design principles including referential integrity, normalization, and indexing to support downstream applications
– Ability to create and execute test plans, strategies and test cases for applications that use ETL components
– Understanding of Data Engineering methodologies: ETL, ELT, data pipeline architecture, etc.
– Knowledge and experience with the 6 dimensions of data quality, and how to track them
– Strong verbal and business communication skills.
Good to have :
– Working experience in AWS or any other cloud service provider
– Data ingestion using one or more modern ETL compute and orchestration frameworks (e.g. Apache Airflow, Luigi, Spark, Apache Nifi or Apache Beam)
– Exposure to data pipeline development or data analytics
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