Senior Data / Analytics Engineer
Posted
Summary
Senior data/analytics engineer building data pipelines, Lakehouse/Warehouse flows, and Power BI semantic models for a US-based client, plus adding GenAI-powered conversational access to data (Fabric Data Agent/Copilot) with accuracy validation. Core stack: Microsoft Fabric, Power BI/DAX, SQL, Python/PySpark; 5+ years' experience and fluent English required.
O projekcie:
Offer:
- Private medical care
- Co-financing for the sports card
- Training & learning opportunities
- Constant support of dedicated consultant
- Employee referral program
Wymagania:
Requirements:
- 5+ years of professional experience
- Hands-on experience with Microsoft Fabric (Lakehouse/Warehouse, pipelines, Dataflows Gen2, notebooks)
- Very good knowledge of Power BI: data modeling, DAX, semantic models
- Good SQL skills and experience with Python/PySpark
- Experience integrating data from various sources (APIs, files, databases, SaaS platforms)
- Experience with or a genuine interest in GenAI solutions for data, including text-to-SQL/DAX, Fabric Data Agents or Copilot, as well as basic knowledge of prompt engineering and LLM response quality evaluation
- Confidence in communicating directly with business stakeholders and independently clarifying unclear requirements
- Ability to think in terms of KPIs and business value
- Proactive and independent approach
- Fluent English for working with a US-based client
Nice to have:
- Experience with reporting on tool adoption, ROI, or digital transformation
- Knowledge of Azure OpenAI / Azure AI Foundry
Codzienne zadania:
Responsibilities:
- Data flows in Microsoft Fabric (ingestion, transformations, data modeling) from multiple sources
- Semantic model and Power BI reports
- Defining AI adoption and business value KPIs together with business stakeholders
- Conversational access to data based on the semantic model (e.g. Fabric Data Agent, Copilot in Power BI, or a custom LLM-based solution)
- Ensuring reliable responses through test question sets, accuracy validation, and clearly defined boundaries regarding the types of questions the solution can handle