Senior Data Engineer

Description

The company is an experience innovation firm working with large consumer brands, with a focus on data, AI, creativity and technology.

The team builds cloud data platforms that support analytics, AI and data products, and the work involves a lot of learning and growth.

The company's value of sharing, caring and daring is part of its culture, and its global, borderless way of working helps teams collaborate across locations.

Responsibilities

• Design, build and optimize modern cloud-based data platforms that support analytics, AI and data products.
• Look into the business problems behind the data, and use analysis and experience to help shape requirements rather than just building what is handed to you.
• Build scalable batch, streaming and near-real-time pipelines that deliver high-quality curated datasets, with strong governance, security and observability.
• Support AI and GenAI systems by building pipelines for machine learning, causal modeling and LLM applications such as RAG and agent-based systems.
• Work closely with data scientists, ML engineers and platform teams.
• Work mainly on AWS and Databricks, with growing GCP work including cloud migration programs, and some Azure or Fabric projects.
• Be staffed on projects that match your strongest platform, with chances to widen your platform skills across clouds.
• Design and implement scalable platforms and pipelines using Spark and Delta Lake, on AWS and Databricks, and on GCP or Azure/Fabric where projects need it.
• Build ingestion, transformation and curation workflows for structured and unstructured data.
• Apply lakehouse patterns and medallion layering (bronze, silver, gold) to create reusable, scalable systems that fit enterprise needs.
• Help with cloud-to-cloud migrations, including re-platforming pipelines and data models.
• Deliver model-ready, production-grade datasets for analytics, ML, causal modeling and optimization.
• Build data flows for GenAI use cases, including LLMs, RAG and vector-based data, and for agent-based architectures.
• Use Databricks MLflow and Unity Catalog, or equivalent tools on other platforms.
• Design logical and physical data models for analytical and operational needs.
• Orchestrate workflows with Databricks Workflows, Airflow, dbt or equivalents such as Azure Data Factory or Cloud Composer, focusing on automation, reliability and maintainability.
• Apply event-driven and streaming architecture patterns.
• Manage data governance, lineage, quality and access control (RBAC/ABAC) using Unity Catalog, AWS Lake Formation or equivalents such as Microsoft Purview or GCP Dataplex.
• Monitor data freshness, pipeline reliability and SLA adherence.
• Build serving layers, such as APIs, feature inputs and analytical endpoints, for downstream ML and AI platforms.
• Keep improving pipelines and infrastructure for performance, scalability and cost.

Requirements

• Ask the right questions to understand not only what stakeholders want but why they want it.
• Point out gaps and better options instead of delivering a brief exactly as written.
• Work closely with data scientists, ML engineers, analysts and business stakeholders.
• Help teams adopt data products and contribute to best practices.
• Strong hands-on experience with Apache Spark and Delta Lake.
• Strong Python and SQL skills.
• Proven experience building batch and streaming pipelines and production-grade data platforms.
• Solid grasp of data modeling, data quality and governance.
• Strong, demonstrable hands-on experience with the Databricks Lakehouse Platform, ideally on AWS (for example S3, Glue, EMR, Redshift, Kinesis, Lambda). This is a key requirement.
• Deep expertise in at least one major cloud (AWS, GCP or Azure/Fabric), plus demonstrable openness and ability to work across clouds.
• Azure/Fabric background (Data Factory, Synapse, Fabric Lakehouse, Azure Databricks) is encouraged, provided you want to work in other clouds too.
• GCP experience (for example BigQuery, Dataflow, Pub/Sub, Cloud Storage, Dataproc) is highly valued, especially in migrations.
• Experience with lakehouse architectures and distributed systems.
• Strong understanding of scalability, reliability and performance.
• Naturally curious, with strong problem-solving skills and a collaborative approach in cross-functional teams.
• Willing to challenge business requirements rather than accept them at face value.
• Adaptable and keen to work across platforms.
• Agile or consulting experience is beneficial.
• Hands-on experience across more than one cloud, or cloud migration experience (for example Azure to GCP) is desirable.
• Snowflake experience is desirable.
• GenAI and AI data systems experience is desirable, including RAG pipelines, vector databases and LLM data preparation.
• CI/CD for data pipelines and infrastructure-as-code (Terraform, CloudFormation) is desirable.
• Streaming technologies (for example Kafka), Spark optimization or ML/experimentation platform experience is desirable.
• Experience building data products or large-scale analytics platforms is desirable.

Conditions

The role is based in Poland.

Remote and hybrid working options are available, depending on country.

The company is committed to inclusion and accessibility, and reviews all applications on skills, experience and potential.

Reasonable accommodations are available during interviews on request.

Benefits

• 24 working days of paid vacation per year.
• National holidays covered.
• Sick leave of up to 20 days per year.
• Unpaid leave of up to 20 days per year.
• Medical insurance.
• Multisport card or multi-cafeteria benefit.
• Maternity and paternity leave support.
• Internal workshops and learning initiatives.
• Reimbursement for professional certifications.
• Participation in local and global professional communities.
• A growth framework that sets out expectations and the steps toward your chosen career path.
• A mentoring program, where you can be a mentor or a mentee to move into a higher position.
• A progressive benefits system, where benefits grow the longer you stay with the company.
• International mobility and professional development programs.
• Access to cutting-edge tools, training and industry experts.