Senior Data Platform Engineer (Databricks, Spark, Python)

Relout is a place created by ambitious people with a passion for technology. We work for international projects and clients from various industries, helping startups, software houses, and enterprises to transform and scale their businesses.

Our mission is to connect best-in-class, passionate engineers with fast-growing digital & technology companies. You’ll be part of the engineering organization with a strong focus on using industry standards and cutting-edge technology.🔥

We are looking for a Senior Data Platform Engineer to join a growing Data Platform team responsible for building and evolving a modern, cloud-native data ecosystem. The platform enables domain teams to create, manage, and scale data products that support analytics, reporting, machine learning, and AI-driven initiatives across the organisation.Operating within a hub-and-spoke model, the central platform team provides shared infrastructure, governance standards, reusable frameworks, and self-service capabilities, while domain teams own and develop their data products independently.

As a Senior Data Platform Engineer, you will play a key role in expanding platform adoption, enhancing core data engineering frameworks, and enabling teams to efficiently deliver reliable and scalable data products. This is a hands-on senior position that combines data engineering, platform architecture, governance, and technical enablement.

🔷Responsibilities:

• Act as a subject matter expert for the Data Platform, providing technical guidance and support to engineering teams.

• Lead onboarding activities, architecture reviews, and technical workshops for teams adopting platform capabilities.

• Design, develop, and continuously improve scalable data ingestion frameworks supporting batch and near real-time processing.

• Build reusable and maintainable data engineering solutions using Databricks, Apache Spark, Python, and SQL.

• Enhance and standardise data product frameworks to support self-service development and accelerate delivery across teams.

• Develop reusable templates, reference implementations, and best practices that improve platform adoption and developer experience.

• Design and implement governance solutions, including data access management, cataloguing, lineage, and secure data sharing.

• Embed data quality, observability, monitoring, and validation capabilities into platform services and frameworks.

• Evaluate emerging platform technologies and new Databricks capabilities, assessing their applicability and business value.

• Drive adoption of approved platform standards, tools, and engineering practices across multiple teams.

• Collaborate with cross-functional stakeholders in an Agile/Scrum environment to deliver scalable and reliable platform capabilities.

• Mentor engineers and promote engineering excellence through knowledge sharing and technical leadership

🎯Requirements:

• 5+ years of experience in Data Engineering, with strong hands-on expertise in modern data platforms.

• Extensive experience with Databricks and Apache Spark (Python and SQL).

• Strong knowledge of data ingestion, transformation, and orchestration patterns in large-scale environments.

• Experience designing and implementing reusable frameworks for data processing and data product development.

• Solid understanding of data governance, access management, data quality, observability, and platform best practices.

• Strong Python programming skills.

• Experience working with cloud-based data platforms, preferably AWS.

• Familiarity with CI/CD practices and modern software engineering principles.

• Experience working in Agile/Scrum delivery teams.

• Excellent communication, collaboration, and stakeholder management skills.

• Ability to coach and support engineering teams in adopting platform capabilities and best practices.

  Nice to Have

  • Experience deploying and managing Databricks on AWS.

  • Knowledge of Data Mesh principles and domain-oriented data ownership models.

  • Experience with Unity Catalog, access control frameworks, and enterprise data governance.

  • Familiarity with Databricks Lakeflow, Auto Loader, Workflows, and AI/BI capabilities.

  • Experience with Databricks Declarative Asset Bundles (DAB).

  • Understanding of FinOps practices, cloud cost optimisation, and serverless compute models.

  • Experience working in platform enablement or internal platform engineering teams.

  • Databricks Certified Professional (Data Engineer or Solution Architect) certification.

⭐What we offer:

• Flexible contract currency of your choice (PLN/EUR/SEK)

• Flexible work arrangements and remote work options

• Professional development and training opportunities

• Collaborative and inclusive work environment

• Opportunity to work on cutting-edge technologies and make a meaningful impact in the dairy industry

• Regular company events and integrations (meetups)

Missing anything you like? Luxmed, Multisport? Ask us about it!

Apply now! Join the Relout Team today! 📢