Job description

Role- ETL / Power BI Engineer (Agentic AI – Claude Code) Location- Princeton, NJ & NYC, NY (Hybrid) Duration- Fulltime Experience: 8+ Years 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.

Requirements

Must-haves

Role- ETL / Power BI Engineer (Agentic AI – Claude Code)
Location- Princeton, NJ & NYC, NY (Hybrid)
Duration- Fulltime
Experience: 8+ Years
Required Skills & Qualifications
7–10+ years in data engineering , ETL development, BI engineering, with strong hands-on in Power BI & AI/ML
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-haves

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.

Application prep

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Keywords to mirror

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Effort: medium