Data Engineer

RITS Group is an IT company offering top-quality programming services for both the Polish and international markets. We are proud to be one of the fastest-growing technology companies. Our priority is the quality and innovation of the solutions we deliver, and our organizational culture is based on trust, collaboration, and continuous improvement.

• Bachelor's Degree
• At least 4 years of experience
• Preference for a field of study such as Management Information Systems, Computer and Information Science, Systems Engineering, Mathematics, or Statistics
• Building pipelines and models on Snowflake and Databricks (SQL, Python, PySpark), with Sigma or a comparable BI tool for delivery
• Integrating data from ERPs, fund administration systems, SharePoint, APIs, and flat files into a validated, analysis-ready model
• Designing reconciliation, validation, and data-quality checks
• Applying dimensional modeling and performance tuning
• Staying hands-on as a senior engineer while coaching a less experienced teammate
• Communicating directly with client data owners, explaining data provenance to non-technical people
• Listening closely to learn unfamiliar source systems and a new domain quickly
• Implementing data anonymization, security, and compliance best practices
• Understanding responsible AI practices where data feeds AI workflows

• Embed with client data owners to discover, profile, and understand source systems, including ERPs, fund admins, SharePoint, and files
• Do the majority of the hands-on build: ingestion, integration, and transformation pipelines that stand up fast and refresh as data validates
• Model data for analysis and build reconciliation and validation checks so outputs tie out and trace back to source
• Deliver dashboards and self-serve views that give the team a trustworthy picture of the data
• Work directly with client stakeholders to explain where the data came from, resolve discrepancies, and build confidence in the numbers
• Coach the second engineer on your pod, teaching as you build and reviewing their work
• Set the data architecture and make practical tooling and build-vs-buy calls for the engagement
• Promote reusable integration, mapping, and validation patterns back to the core platform
• Safeguard data quality, security, and compliance throughout the engagement