Data Analyst (PySpark)

Location: Poland; work from the European Union region and a work permit are required.

Company

Global AI, digital transformation, and engineering partner delivering scalable products, platforms, data-driven solutions, and cloud services across 16 countries.

What you will do

• Analyze large datasets covering customer behavior, digital marketing campaigns, and business performance.
• Design, develop, and maintain analytical datasets using SQL and PySpark.
• Prepare and transform data from multiple sources for reporting and advanced analytics.
• Support campaign measurement, customer segmentation, funnel analysis, retention, churn, and ROI calculations.
• Collaborate with marketing analysts, business stakeholders, and data teams to translate business questions into insights.
• Ensure data quality and reliability, investigate issues, and improve data models and processing workflows.

Requirements

• 3+ years of experience as a Data Analyst, Analytics Engineer, or in a similar data-focused role.
• Advanced SQL skills, including complex joins, CTEs, window functions, and query optimization.
• Hands-on experience with PySpark and large-scale datasets.
• Strong analytical, problem-solving, and data interpretation skills.
• Ability to work independently in a fast-paced environment.
• Fluent Polish and English; work from the European Union region and a valid work permit are required.

Nice to have

• Experience in digital marketing analytics, customer acquisition, retention, campaign performance, funnel conversion, or customer lifetime value analysis.
• Experience with Databricks, Delta Lake, or modern lakehouse architectures.
• Understanding of data modeling concepts and familiarity with Power BI.
• Experience working in agile teams.

Culture & Benefits

• Engineering-focused environment with a consulting mindset.
• People-first culture centered on growth and knowledge sharing.
• Exposure to modern technologies including AWS, Azure, GCP, Databricks, and Snowflake.
• Collaboration with international data, engineering, marketing, and business teams.

Hiring process

• CV review.
• HR call followed by an interview and client interview.
• Final decision.