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# Data Engineer

- **Company:** Postaladdress
- **Location:** Spain (Remote available)
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, BigQuery, Cloud Computing, Information Engineering, Data Transformation, Data Warehousing, Python (Programming Language), Operational Databases, DataOps, SQL Databases, Data Streaming, Snowflake, Technical Debt, Backend, Data Analytics, Code Restructuring, Databricks
- **Published:** July 17, 2026
- **Apply:** https://www.jobleads.com/es/job/e1f7d71a2044e27b508f07887e5af2574

## About the Role

* Minimum of 5 years of experience in data engineering roles, ideally within B2B SaaS companies or product-led startup environments.
 * Strong proficiency in Python and SQL, with the ability to apply both languages to complex engineering and data challenges.
 * Proven experience building, deploying, and operating production data pipelines on AWS.
 * Hands-on expertise with modern data warehouse technologies such as Snowflake, BigQuery, Databricks, or Redshift.
 * Experience using DBT or similar data transformation frameworks.
 * Solid understanding of backend engineering principles, with the ability to review and contribute to application code when required.
 * Comfortable taking ownership of projects end-to-end within dynamic, fast-growing teams.
 * Strong communication, collaboration, and problem-solving skills, combined with a product-oriented mindset.

## Description

* Own and continuously enhance the company's data platform, including warehouse architecture, modelling strategies, and transformation frameworks.
 * Design, build, and maintain scalable production data pipelines using modern cloud technologies and engineering best practices.
 * Refactor and improve critical data flows to reduce technical debt, strengthen system integrity, and increase platform reliability.
 * Collaborate closely with backend engineers to ensure data is generated, structured, and exposed correctly at the source.
 * Partner with product and engineering stakeholders to enable data-driven features, telemetry, instrumentation, and customer-focused outcomes.
 * Implement observability, testing, and monitoring processes to ensure robust and dependable data operations.
 * Contribute to backend initiatives where data engineering and product development intersect, acting as an embedded engineering partner rather than a standalone analytics function.


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