Data & Analytics Engineer

Job Title: Data & Analytics Engineer Experience: 3-4 years Location: Remote Employment Type: Full-time Team: Data Engineering & Analytics

Eltropy is a digital conversations platform for credit unions and community financial institutions in the US. The Data Engineering & Analytics team builds the AWS data pipelines and customer-facing dashboards that power analytics across the platform.

We are looking for a Data & Analytics Engineer with 3-4 years of experience who can own dashboard delivery end to end along with the pipelines behind it. The ideal candidate learns fast, builds product context quickly, listens well, and collaborates effectively across product, engineering, DevOps, and customer-facing teams.

• →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.
• →Write and optimize Redshift SQL; debug query performance, connection contention, and data mismatches across sources.
• →Support near-real-time ingestion (Kafka/MSK CDC → Glue Streaming → S3 → Redshift).
• →Investigate customer-reported analytics discrepancies (Jira/support tickets), root-cause them in the data, and communicate findings clearly to support, product, and engineering.
• →Set up and respond to pipeline monitoring - CloudWatch metrics and alarms, monitoring DAGs, refresh health - and participate in incident triage and RCA.
• →Develop deep product knowledge: understand what each metric means to our credit union customers and translate product changes into data model and dashboard updates.
• →Ensure data quality, validation, and consistency across systems.

• →Adhere to Eltropy's policies on security, confidentiality, availability, and privacy; handle customer and financial-institution data responsibly, protect access credentials, and report security events promptly through Eltropy's channels.

• 3-4 years of experience in data engineering and/or analytics engineering.
• Strong SQL on Redshift (or a similar MPP warehouse) and solid Python/PySpark.
• Hands-on experience with the AWS data stack: S3, Glue, Redshift, CloudWatch.
• Workflow orchestration with Apache Airflow — authoring, debugging, and deploying DAGs.
• Data modeling and warehousing fundamentals.
• BI dashboarding experience with QuickSight, ThoughtSpot, Tableau, or Power BI.
• Quick learner — able to grasp an unfamiliar product and data model fast and work independently.
• Strong listening and collaboration skills; comfortable coordinating across product, engineering, DevOps, and customer-facing teams.

• Streaming/CDC experience: Kafka (MSK), Debezium, Spark Structured Streaming.
• AWS infrastructure awareness: IAM roles, security groups, Secrets Manager, Kinesis/Firehose.
• Fintech or B2B SaaS analytics exposure.