Analytics Engineer - Senior Analyst
- Posted
- Employment
- full time
- Work mode
- hybrid
Skills explicitly mentioned: SQL, Python, ETL, ELT, Databricks, Power BI, DAX, Data Modeling, Snowflake, Redshift, Azure Data Factory, AWS Glue, CI/CD
Location: Bangalore India - Outer Ring Road Work arrangement: Hybrid Time type: Full time Posted: 5 days before the 2026-08-31 audit Requisition: JR-0016357 Position level: Senior Analyst Country: India
Role summary The Data & Analytics Senior Analyst works with Data Engineers, Power BI Developers, Data Architects, QA, product owners, and business stakeholders to design, develop, test, deploy, and support Huron's enterprise analytics and reporting solutions. The role combines hands-on data engineering with Power BI and business-intelligence development across Corporate IT, Software Development, and business teams in India and the US. It owns full-lifecycle delivery of data pipelines, curated datasets, semantic models, dashboards, reports, testing, tuning, documentation, deployment, and remediation.
Responsibilities - Design and support ETL/ELT pipelines, data models, curated datasets, semantic models, dashboards, and reports. - Build scalable pipelines using SQL, Python, Databricks, cloud data services, and analytical databases. - Develop Power BI reports, DAX calculations, relationships, measures, drill-throughs, and security-aware reporting structures. - Work across Databricks, warehouses, lakes, APIs, files, and relational databases to create reusable reporting-ready data. - Define metrics, data mappings, source-to-target logic, test plans, release notes, and support documentation. - Troubleshoot quality, refresh, DAX, access, visualization, pipeline, and report-performance problems. - Support code review, CI/CD, UAT, data governance, security, and reusable delivery assets.
Preferred background Two to four years in data or analytics engineering, BI, Power BI, reporting, or data-platform delivery; strong SQL, Python, ETL/ELT, validation, modeling, dimensional design, Databricks, Snowflake, Redshift, SQL Server, or PostgreSQL; Power BI semantic models and DAX; cloud services such as Azure Data Factory, AWS S3, Glue, Lambda, Athena, Redshift, and RDS; Git and Azure DevOps.