Data Engineer
Kraków - Poland, Polska
Key offer highlights
Data: SQL / BI / Python
DevOps / Cloud: AWS, Azure, Docker, Kubernetes
Hybrid model - partly remote
Full-time
Private healthcare
Description
Compensation details will be shared by the recruiter during the first interview.
The Perks
Competitive salary & benefits plan
Life Insurance
My Benefit Platform
Medical Insurance with Medicover
1 additional day off to celebrate your Birthday
2 additional days off a year for voluntary work
Share Plans for Employees
Free lunch at the office (ones per week)
Employee Assistance Program
We work in hybrid working model
What you’ll do
Design and build robust batch and real-time data pipelines on GCP, including Kafka-based event streams, BigQuery transformations, and Airflow-orchestrated workflows, as part of the GCP consolidation and Medallion architecture build-out
Own data quality within your delivery area: define and implement data contracts, quality checks, and observability instrumentation so that pipeline health is visible and SLAs are met
Develop and maintain in-house connectors and third-party native integrations that form part of IG’s ingestion estate, ensuring resilience, monitoring, and long-term maintainability
Contribute to engineering standards and best practices across the squad — including code review, dbt modelling patterns, CI/CD pipeline hygiene, and change control for shared datasets
Support feature engineering and model data pipelines for Data Science, and help lay the foundations for AI-ready data — including lineage, reproducibility, and freshness guarantees for ML workloads
What you’ll need for this role
Proven hands-on experience building and operating production-grade data pipelines on GCP — including BigQuery, Cloud Composer/Airflow, GCS, and Cloud Run — with strong SQL and Python skills
Solid experience with Apache Kafka or equivalent streaming technologies, including designing event-driven ingestion patterns and troubleshooting real-time data flows under operational conditions
Familiarity with modern transformation tooling, particularly dbt, and an appreciation of Medallion (Bronze/Silver/Gold) architecture patterns and how they support self-service analytics
A quality-first mindset: experience implementing data contracts, lineage tracking, observability tooling, and pipeline SLO monitoring in a production environment
Comfortable working in a regulated financial services environment, with an understanding of data governance requirements (lineage, access control, audit trails) and the discipline to operate within change control processes