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itD
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ETL
Responsibilities:
- Own dashboard changes end to end in QuickSight and ThoughtSpot — new metrics and filters, SPICE refresh management, internal-to-production promotion, and post-release validation.
- Build and maintain batch and streaming ETL pipelines on AWS using Glue (PySpark), S3, Redshift, and Airflow (MWAA) DAGs.
- Support near-real-time ingestion (Kafka/MSK CDC → Glue Streaming → S3 → Redshift).
Required Skills:
- 3-4 years of experience in data engineering and/or analytics engineering.
- Strong SQL on Redshift and solid Python/PySpark.
- Hands-on experience with the AWS data stack: S3, Glue, Redshift, CloudWatch.
Team Culture:
- You will work with a Data Engineering & Analytics team that builds product context quickly and collaborates across product, engineering, DevOps, and customer-facing teams.
- The role emphasizes listening well, working independently, and making the most of AWS infrastructure to deliver analytics that matter to credit union customers.
Eltropy
Eltropy is a digital conversations platform for credit unions and community financial institutions in the US. The Data Engineering & Analytics team builds AWS data pipelines and customer-facing dashboards that power analytics; they seek a collaborative engineer who learns fast and works across teams.