Data Engineer Power BI

Data Engineer - Power BI Modelling Level: Senior to Advanced - 5-15 years Locations: Mumbai / Bengaluru Joining an existing data engineering squad, you own Power BI semantic modeling on top of PySpark/SQL pipeline engineering, delivering enterprise-grade reporting and analytics. As an embedded Data Engineer, you turn PySpark pipelines into trusted Power BI models for the business. Note: Shares a common PySpark/Snowflake base with "Data Engineer - Graphing" - source together, differentiate on semantic-modeling vs. graphing depth at interview. Key responsibilities - Model semantically. Build and maintain Power BI semantic models (DAX, star schemas) for enterprise reporting. - Build pipelines. Develop PySpark/Python and SQL pipelines feeding the Snowflake environment. - Partner with stakeholders. Translate reporting requirements into performant data models. - Ensure data quality. Validate accuracy and performance of models and underlying pipelines. - Collaborate. Operate inside the existing squad with no separate delivery lead required. - Explore GenAI. Apply GenAI techniques to reporting and data use cases as opportunities arise. Must-have qualifications - Python and PySpark - SQL - Power BI semantic modeling (DAX, data modeling) Preferred - Snowflake; Dataiku - GenAI exposure What success looks like – first 6 to 12 Months - Power BI models adopted for key reporting use cases - Reliable PySpark/SQL pipelines feeding those models - Smooth integration into the existing squad Confidential – Wissen Technology Skills:- Data engineering, PowerBI, Python, PySpark and SQL