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 (€ 55000 - € 65000)
- Work in a friendly and diverse team
- private health insurance
- gym membership
- learning opportunities
- flexible benefits
- team events
- free office snacks and drinks
Baxter Planning is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. Baxter Planning is also committed to compliance with all fair employment practices regarding citizenship and immigration status.
Skills Required
- 4+ years building and operating production data pipelines
- Strong Python programming skills
- Experience with AWS services including S3, Glue, Athena, Redshift, Lake Formation, CloudWatch, DMS, Lambda, Step Functions, SQS/SNS, ECS, DynamoDB, and CloudFormation
- Experience with lakehouse tables such as Delta Lake or similar
- Experience with schema evolution, partitioning, compaction, and upserts or merge operations
- Solid data modeling skills, including star schema design
- Experience implementing testing, data quality, and observability practices
- Experience running AWS DMS in production, including monitoring and troubleshooting
- Experience developing ETL or ELT pipelines with Polars
- Experience with async programming or concurrency in Python
- Experience with Apache Airflow and AWS-native orchestration tools
- Experience with CI/CD and infrastructure as code
What We Do
Baxter Planning provides solutions built for the service supply chain. Our software is developed based on proven best practices, industry expertise, and partnerships with our customers to automate inventory planning. We replace spreadsheets and manual processes with a Total Cost Optimization methodology to deliver the best service level at the lowest possible cost. Global clients deploying our software include: Avaya, Ciena, Extreme Networks, NetApp, Bio-Rad, and more.
