About the role
Required Skills & Qualifications
7–10+ years in data engineering , ETL development, BI engineering, with strong hands-on in Power BI & AI/ML
Expertise in:
SQL (complex queries, optimization, window functions).
DAX (measures, calculated columns, time intelligence, performance tuning).
Data modeling (star/snowflake schemas, semantic layers).
Solid experience building ETL/ELT pipelines in cloud environments (Azure: ADF, Databricks, Synapse; or AWS/GCP equivalents).
Proficient in Python and/or Spark for data transformation and automation.
Hands-on experience using Claude Code (or similar agentic IDEs) for real data engineering tasks: generating code, tests, refactors, and documentation.
Familiarity with agentic patterns: skills, prompts, MCP connectors, and integrating AI agents into CI/CD or data workflows.
Strong understanding of data quality, governance, and security in analytics platforms (RLS, workspace roles, deployment pipelines).
Nice-to-Have
Experience with dbt, Data Factory, Databricks, Snowflake, or Fabric.
Exposure to Power BI agent skills / Skills for Fabric or similar AI-assisted report-building capabilities.
Background in knowledge graphs / ontologies or advanced metadata management.
Certifications: Microsoft PL-300 (Power BI Data Analyst), DP-600 (Fabric Analytics Engineer), Databricks, or cloud data engineering certs.