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.

Responsibilities:

• 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 

We are looking for:

• 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, and caring whether the data actually ties out

• Applying dimensional modeling and performance tuning to stand up trustworthy data quickly

• Staying hands-on as a senior engineer while coaching a less experienced teammate

• Communicating directly with client data owners, asking the right questions, and 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 in client environments

• Understanding responsible AI practices where data feeds AI workflows