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Data Engineer
JOB SUMMARY
Roles
Job details
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 doBuild 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 for4+ 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 teamprivate health insurance
• gym membership
• learning opportunities
• flexible
benefits
• team events.
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 doBuild 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 for4+ 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 teamprivate health insurance
• gym membership
• learning opportunities
• flexible
benefits
• team events.
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Baxter Planning Spain
