Senior Data Engineer
CZE - Central Bohemian - Prague (Five)CompetitiveHybridFull time0 applicants
About this role
Job Description
We're looking for a hands-on Data Engineer who genuinely enjoys the craft — someone who writes SQL and Python every day, takes pride in pipelines that just work, and wants their code to matter. The transformations you build here won't sit in a sandbox. They'll feed the analytics, reporting, and decisions that help protect our company.
This isn't a role for learning the fundamentals on the job. It's a role for someone who already has them and wants the space to do their best work.
Responsibilities
- Data transformation and engineering
- Design, write, and maintain high-quality SQL and Python for data transformations across development and production environments.
- Implement DDL and advanced data operations: enrichment, cleansing, parsing, normalization, and schema evolution.
- Own existing transformations and continuously improve them as data volume, variety, and complexity grow.
- Write code that is readable, testable, and maintainable, so other engineers can understand, extend, and support it.
- Platform and pipeline execution
- Work hands-on with cloud data services such as AWS (Glue, Lambda, Redshift), GCP (BigQuery, Dataflow, Cloud Functions), or equivalent platforms such as Azure Data Factory.
- Build and operate reliable, automated pipelines deployed through our Terraform-based CI/CD setup.
- Partner with platform, DevOps, and analytics teams to ensure smooth deployment, monitoring, and day-to-day operation of data workloads.
- Databricks experience is a plus, not a requirement.
- Engineering quality and collaboration
- Apply core engineering disciplines: version control (Git), code review, and structured change management.
- Communicate clearly about data logic, assumptions, and trade-offs with both technical and non-technical stakeholders.
- Contribute to shared standards and best practices for SQL, Python, and ETL development.
- Operate with the data quality, reliability, and compliance discipline expected in a regulated enterprise environment.
- What you bring
- Primary skills:
- Data engineering, AWS, GCP/BigQuery, IaC, data lakes, GitHub, pipeline management
- Secondary skills:
- DevOps collaboration, general scripting
Requirements
- Bachelor's degree in Computer science, Information Technology, or equivalent experience.
- 5+ years building data pipelines and data infrastructure, ideally in the context of GRC.
- Strong, practical SQL and Python skills, specifically for data transformation and ETL.
- A track record of building and maintaining production pipelines — not just prototypes or coursework.
- Solid grasp of relational data modelling, normalization, and performance-aware SQL design (including warehouse-style SQL such as BigQuery or Redshift).
- Hands-on experience with at least one cloud data platform (AWS, GCP, or Azure).
- Comfort with Git-based workflows and automated deployment pipelines.
- Clear thinking about data problems, expressed in clean, maintainable code.
Nice to have
- Experience across multiple cloud data platforms (e.g., AWS
- and
- GCP/BigQuery).
- Experience in regulated or enterprise environments (healthcare, life sciences, finance).
- Exposure to Databricks, Spark, or large-scale analytical workloads.
- Working familiarity with infrastructure-as-code (e.g., Terraform) as a consumer.
- Experience supporting analytics, reporting, or data science teams as downstream consumers.