Data Engineer

Capco; Kraków; Hybrid; PLN 180,000 - 240,000; Full time

Job summary

Capco Poland is seeking a Mid Data Engineer to join our growing data engineering team and contribute to scalable data solutions for financial clients.

You will work with modern data technologies and cloud platforms, developing and maintaining data pipelines, processing large datasets, and supporting enterprise-scale data solutions.

This role is ideal for someone with hands-on experience in Python, Spark, Hadoop, Linux, and Google Cloud Platform while collaborating on international projects.

Qualifications

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

Responsibilities

• Design, develop, and maintain scalable data pipelines and processing solutions.
• Build data transformation workflows using Python and Spark.
• Work with large-scale datasets in distributed environments like Hadoop.
• Develop cloud-based data solutions on Google Cloud Platform.
• Create reliable ingestion processes from multiple source systems.
• Implement data transformations, validation, and quality checks.
• Troubleshoot pipelines and optimize performance.
• Work with Linux-based environments, scripting, and deployment tasks.
• Collaborate with data engineers, architects, and analysts to translate requirements.
• Participate in code reviews and follow best practices in data engineering.
• Document data flows, dependencies, configurations, and operations.
• Support deployment, testing, stabilization, and maintenance of data solutions.

Skills

Python

Apache Spark

Hadoop

Linux

GCP

SQL

English (B2)

Git

Agile

Data pipelines

Tools

Google Cloud Platform (GCP)

Apache Airflow

Docker/Kubernetes

BigQuery

Dataproc/Dataflow

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.