Job Description
Key job responsibilities
• Design, implement, and support data warehouse / data lake infrastructure using AWS big data stack, Python, Redshift, Quicksight, Glue/lake formation, EMR/Spark/Scala, Athena etc.
• Extract huge volumes of structured and unstructured data from various sources (Relational /Non-relational/No-SQL database) and message streams and construct complex analyses.
• Develop and manage ETLs to source data from various systems and create unified data model for analytics and reporting
• Perform detailed source-system analysis, source-to-target data analysis, and transformation analysis
• Participate in the full development cycle for ETL: design, implementation, validation, documentation, and maintenance.
• Drive programs and mentor resources to build scalable solutions aligning to team’s long term strategy
Basic Qualifications
– 3+ years of data engineering experience
– Experience with data modeling, warehousing and building ETL pipelines
Preferred Qualifications
– Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
– Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)