As a Data Engineer at Baxter Planning you will play a key role in building and evolving our data lake platform, supporting analytics and data-driven products across the business. You will design and operate reliable, production-grade data pipelines and curated datasets using modern AWS services and Python. This role focuses on data modeling, data quality, and near-real-time ingestion to ensure trustworthy, BI-ready data. You will work closely with engineers and stakeholders while contributing to architecture, automation, and best practices. What you’ll do • Build the data-serving layer: curated datasets, marts, and product-ready tables • Develop incremental / micro-batch pipelines and support CDC near-real-time ingestion (AWS DMS) • Design BI-friendly data models (star schema) and manage schemas • Build ETL/ELT in Python (Polars) and serve/query via Athena and/or Redshift • Implement data quality observability (freshness, completeness, duplicates, schema drift, anomalies) • Orchestrate with Airflow and AWS-native tools (e.g., Step Functions) • Contribute to CI/CD, IaC, architecture discussions, and best practices What we’re looking for • 4 years building and operating production data pipelines • Strong Python (async/concurrency is a plus) • Strong AWS across services like: S3, Glue, Athena, Redshift, Lake Formation, CloudWatch, DMS, Lambda, Step Functions, SQS/SNS, ECS, DynamoDB ( CloudFormation) • Experience with lakehouse tables (Delta or similar), schema evolution, partitioning, compaction, upserts/merge • Solid data modeling skills (star schema) and commitment to testing & data quality • Experience running AWS DMS in production (monitoring/troubleshooting) What we offer • A competitive salary • Work in a friendly and diverse team • private health insurance • gym membership • learning opportunities • hybrid model of work • flexible benefits • team events Powered by JazzHR