BI Data Engineer (part time) @ ITFS Sp. z o.o.

• Workplace: 100% remote (working aligned to UK business hours)
• Start: September 2026
• Cooperation form: B2B with ITFS
• Rate: 120-150 PLN/h + VAT
• Work model: 3 days per week (preferred: Monday, Wednesday and Thursday), with flexibility in scheduling as long as agreed turnaround times are met and availability is ensured for urgent requests, quick fixes, data extracts and visualizations
• Recruitment process: Short phone call with ITFS recruiter -> Technical/project interview with Client -> Decision

• Min. 4 years of experience in a similar role
• Data Engineering Expertise: Strong background in building and maintaining cloud data pipelines and ETL processes.
• Azure Stack Expertise: Proven hands-on experience in the Microsoft Azure data ecosystem.
• Data Orchestration: Experience with Mage (or similar orchestration engines like Airflow/Prefect) and Adverity.
• Languages & Querying: Proficiency in Python and SQL for pipeline modifications and data extraction.
• Communication: Clear, candid, and concise English communication skills (capable of engaging in technical discussions with internal stakeholders or clients).

• Workplace: 100% remote (working aligned to UK business hours)
• Start: September 2026
• Cooperation form: B2B with ITFS
• Rate: 120-150 PLN/h + VAT
• Work model: 3 days per week (preferred: Monday, Wednesday and Thursday), with flexibility in scheduling as long as agreed turnaround times are met and availability is ensured for urgent requests, quick fixes, data extracts and visualizations
• Recruitment process: Short phone call with ITFS recruiter -> Technical/project interview with Client -> Decision

,(Pipeline Maintenance & Support: Monitor, maintain, and troubleshoot existing data pipelines and flows across Azure and Mage., Data Visualization & Reporting: Support day-to-day reporting and visualization requests using Adverity (primary ETL and front-end platform) and occasionally PowerBI., System Operations: Address back-end data flow issues, data cleansing, standardization, and taxonomy/normalization updates., Team & Technical Support: Serve as a technical point of contact for client side internal teams and participate in client-facing technical discussions if necessary., Knowledge Transfer: Participate in onboarding/handover with the departing team member in September and help document workflows for the incoming permanent hire.) Requirements: Data engineering, Cloud, Data pipelines, Azure, Airflow, Python, SQL, ETL, Adverity, AI Additionally: Sport subscription, Private healthcare, International projects.