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

versátil 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.

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📌 Data Engineer (Madrid)
🏢 Baxter Planning Systems
📍 Madrid