Senior Data Engineer – GCP, Kraków, Flexible B2B
Capco Poland, a technology and management consultancy serving financial institutions, is hiring a mid/senior data engineer in Kraków to design, build, and maintain scalable data pipelines and cloud data solutions for banking clients. Core stack: Python, Apache Spark, Hadoop, Linux, and Google Cloud Platform, on a flexible B2B contract.
- Compensation
- Not disclosed
- Location
- Kraków, Poland
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Contract
- Experience
- 6+ years
- Category
- Data engineering
- Posted
Skills
Must have
- 4-6+ years of commercial experience in Data Engineering or similar role
- Good hands-on programming skills in Python
- Practical experience with Apache Spark, including building/maintaining data processing jobs
- Experience with Hadoop or distributed data processing ecosystems
- Good knowledge of Linux and command-line environments
- Commercial experience with Google Cloud Platform (GCP) and relevant data services
- Good understanding of ETL/ELT processes, data pipelines, and data transformation concepts
- Working knowledge of SQL and relational data concepts
- Understanding of data quality, monitoring, and troubleshooting practices
- Familiarity with Git and modern software development practices
- Ability to work effectively in Agile environment with distributed teams
- Good communication skills and English at minimum B2 level
Nice to have
- Experience with GCP services such as BigQuery, Cloud Storage, Dataproc, Dataflow, or Pub/Sub
- Experience in Financial/Banking domain
- Experience with orchestration tools such as Apache Airflow
- Familiarity with CI/CD processes for data solutions
- Knowledge of data modelling and data warehouse concepts
- Experience working with financial services or banking clients
- Familiarity with containerization technologies such as Docker or Kubernetes
Full description
We offer a flexible collaboration model based on a B2B contract, with the opportunity to work on innovative AI and automation initiatives for leading financial institutions.
At Capco Poland, we’re not just another consultancy – we’re the spark behind digital transformation in the financial world. As a global leader in technology and management consulting, we help our clients tackle complex challenges across banking, payments, capital markets, wealth, and asset management.
Our secret?
A culture that’s fast, flexible, and fiercely entrepreneurial. We move quickly, think creatively, and always put our people first.
We’re passionate about growth – both for our clients and ourselves – and that means attracting talented professionals who want to develop their skills, take ownership, and make a real impact.
We’re proud to be:
Trailblazers in banking, payments, capital markets, wealth, and asset management
Champions of an agile, nimble, and innovative work environment
Dedicated to building a team of talented professionals who share our drive and vision
THE ROLE
We are looking for a strongMid/Senior Data Engineer to join our growing data engineering team and contribute to building scalable, reliable data solutions for our financial services clients.
You will work with modern data technologies and cloud platforms, developing and maintaining data pipelines, processing large datasets, and supporting the delivery of enterprise-scale data solutions.
This is a great opportunity for a Data Engineer who already has hands-on commercial experience and wants to further develop their expertise in Python, Apache Spark, Hadoop, Linux, and Google Cloud Platform (GCP) while working on complex international projects.
WHAT YOU’LL DO
Design, develop, and maintain scalable data pipelines and data processing solutions.
Develop data transformation and processing workflows using Python and Apache Spark.
Work with large-scale datasets in distributed environments using Hadoop and related technologies.
Build and support cloud-based data solutions on Google Cloud Platform (GCP).
Develop reliable ingestion processes integrating data from multiple source systems.
Implement data transformations, validation rules, and data quality checks.
Troubleshoot data pipeline issues and support performance optimization.
Work with , including scripting, deployment, and operational activities.