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# Data Engineer

- **Company:** Baxter
- **Location:** Barcelona, Spain
- **Salary:** €55,000.0 - €65,000.0
- **Contract:** Permanent contract
- **Skills:** Airflow, Amazon Web Services, Amazon S3, Continuous Integration, Extract Transform Load (ETL), Amazon DynamoDB, Python (Programming Language), Operational Databases, Concurrency, Cloudformation, Data Lakes, Data Analytics, Star Schema, Cloudwatch, Amazon Simple Queue Service (SQS), Data Pipelines
- **Published:** October 16, 2026
- **Apply:** https://www.adzuna.es/details/5929644844

## About the Role

* 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)

## Description

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