Data Engineer (hybrid)

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