Analytics Engineer - Analyst
- Posted
- Employment
- full time
- Work mode
- hybrid
Skills explicitly mentioned: SQL, Python, ETL, ELT, Power BI, DAX, Data Modeling, Databricks, Azure Data Factory, AWS Glue, Snowflake, Data Warehousing
Location: Bangalore India - Outer Ring Road Work arrangement: Hybrid Time type: Full time Posted: 6 days before the 2026-08-31 audit Requisition: JR-0016367 Position level: Analyst Country: India
Role summary The Data & Analytics Analyst works with Data Engineers, Power BI Developers, Data Architects, QA teams, team leads, and business stakeholders to support Huron's enterprise analytics and reporting solutions. This early-career role builds foundational capability across data engineering, business intelligence, data modeling, reporting, and analytics delivery. It supports Software Development, Corporate IT, and business teams across India and the US through requirements support, data analysis, preparation, report development, testing, documentation, deployment, and production issue remediation.
Responsibilities - Build and maintain data pipelines, datasets, semantic models, dashboards, and reports for enterprise decision-making. - Support ETL and ELT extraction, transformation, loading, mapping, reconciliation, and validation. - Write SQL queries and Python scripts for data preparation, automation, validation, and reporting. - Develop Microsoft Power BI reports, dashboards, semantic models, relationships, measures, filters, and introductory DAX. - Work with cloud platforms, databases, Databricks, data warehouses, lakes, and lakehouse systems. - Participate in requirements, QA, UAT, data-quality, refresh, access, and report-performance troubleshooting. - Maintain technical notes, mappings, report logic, test evidence, user guides, and operational instructions.
Preferred background A bachelor's degree in engineering, information systems, data analytics, business analytics, or related study; zero to two years in data engineering, analytics, BI, or software project work; relational databases, SQL, joins, data models, ETL/ELT, Python, Power BI, visualization, semantic modeling, and exposure to Azure Data Factory, AWS S3/Glue/Redshift, Snowflake, or Databricks.