Mid/Senior Data Engineer (Kraków/GCP)

Capco; Kraków; On-site; PLN 140,000 - 210,000; Full time

Job summary

Capco Poland is seeking a Mid Data Engineer to join their growing data engineering team in Kraków. You will design, build, and maintain scalable data pipelines and cloud-based solutions for financial services clients, using Python, Spark, Hadoop, Linux, and GCP.

This role focuses on hands-on data processing and collaboration across distributed teams on enterprise-scale projects. You’ll contribute to data transformations, ingestion, quality checks, and performance tuning while embracing Agile

Qualifications

• 2–4+ years of commercial experience in Data Engineering or a similar role.
• Strong programming skills in Python.
• Hands-on experience with Apache Spark and building data processing jobs.
• Experience with Hadoop and distributed data processing ecosystems.
• Good knowledge of Linux and command-line environments.
• Commercial experience with Google Cloud Platform (GCP) and data services.
• Understanding of ETL/ELT, data pipelines, and data transformation concepts.
• Working knowledge of SQL and relational data concepts.
• Familiarity with Git and modern software development practices.
• Ability to work in Agile environments with distributed teams.
• Good English communication skills (minimum B2).

Responsibilities

• Design, develop, and maintain scalable data pipelines and processing solutions.
• Develop data transformations and processing workflows using Python and Spark.
• Work with large-scale datasets in distributed environments using Hadoop.
• Build and support cloud-based data solutions on Google Cloud Platform.
• Develop reliable ingestion processes from multiple source systems.
• Implement data quality checks and monitoring practices.
• Troubleshoot data pipeline issues and optimize performance.
• Collaborate with Data Engineers, Architects, Analysts, and stakeholders.
• Participate in code reviews and follow data engineering best practices.
• Create and maintain technical documentation of data flows and configurations.
• Support deployment, testing, and ongoing maintenance of data solutions.

Skills

Python

Apache Spark

Hadoop

Linux

Google Cloud Platform (GCP)

SQL

Git

Apache Airflow

Docker

Kubernetes

ETL/ELT concepts

Tools

BigQuery

Cloud Storage

Dataproc

Dataflow

Pub/Sub

Airflow

Job 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 Mid 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 Linux-based environments, including scripting, deployment, and operational activities.

Collaborate with Data Engineers, Architects, Analysts, and other project stakeholders to translate business requirements into technical solutions.

Participate in code reviews and follow software engineering and data engineering best practices.

Create and maintain technical documentation covering data flows, dependencies, configurations, and operational procedures.

Support deployment, testing, stabilization, and ongoing maintenance of data solutions.

WHAT WE’RE LOOKING FOR

2-4+ years of commercial experience in Data Engineering or a similar role.

Good hands-on programming skills in Python.

Practical experience with Apache Spark, including building and maintaining data processing jobs.

Experience working 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 an Agile environment and collaborate with distributed teams.

Good communication skills and English at a 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.

ONLINE RECRUITMENT PROCESS

Screening call with the Recruiter

Hiring Manager Technical Interview

Client Interview

Feedback / Offer