Senior Data Engineer

Senior Data Engineer - SpainA senior-level role focused on building and scaling a modern data ecosystem that supports product innovation, analytics, and intelligent user experiences. The position offers responsibility for the end?to?end data platform, from warehouse architecture and transformation layers to production?grade pipelines and infrastructure, in a fast?paced, mission?driven environment.AccountabilitiesOwn 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.RequirementsMinimum 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.BenefitsCompetitive salary package and equity participation opportunities.25 days of annual leave in addition to public holidays.Pension contribution scheme.Fully equipped home?office and hardware setup from day one.Regular company off?sites and social events.Flat organizational structure with transparent communication and direct access to leadership.Inclusive and collaborative working culture that values diversity, innovation, and individual perspectives.#J-*****-Ljbffr

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.

Competitive salary package and equity participation opportunities. 25 days of annual leave in addition to public holidays. Pension contribution scheme. Fully equipped home?office and hardware setup from day one. Regular company off?sites and social events. Flat organizational structure with transparent communication and direct access to leadership. Inclusive and collaborative working culture that values diversity, innovation, and individual perspectives. #J-*****-Ljbffr