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Analytics Engineer - Senior Analyst

Huron
Bengaluru, IND
Full-time
Entry · 2+ years experience
Hybrid
Discovered 3 weeks ago
SQLPythonDatabricksPower BIDAXAWS Glue
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Key Responsibilities

  • Design, develop, test, and support Data & Analytics solutions, including ETL/ELT pipelines, data models, curated datasets, semantic models, dashboards, and reports.
  • Build and maintain scalable data pipelines using SQL, Python, Databricks, cloud data services, and relational or analytical databases.
  • Develop and optimize Power BI reports and dashboards that translate business requirements into actionable insights, interactive visuals, and standardized reporting experiences.
  • Build and maintain Power BI data models, relationships, measures, calculated columns, DAX logic, report pages, filters, drill-throughs, and security-aware reporting structures.
  • Work with data from Databricks, cloud data platforms, data warehouses, APIs, files, and relational databases to create reusable reporting-ready datasets.
  • Partner with Product Owners, BI Developers, Data Engineers, QA, and stakeholders to clarify requirements, define metrics, validate business logic, and align report outputs to business definitions.
  • Create technical specifications, data mappings, source-to-target logic, test plans, deployment notes, and support documentation based on conceptual designs and business requirements.
  • Independently troubleshoot data quality, data refresh, semantic model, DAX, visualization, access, pipeline, and report performance issues.
  • Support peer reviews, code reviews, pull requests, release readiness, and deployment validation using Git, Azure DevOps, and CI/CD practices where applicable.
  • Collaborate closely with QA to validate data accuracy, visual behavior, dashboard functionality, model relationships, and defect remediation.
  • Support UAT cycles by preparing validation evidence, explaining report logic, resolving defects, and coordinating with business stakeholders.
  • Ensure solutions follow Huron standards for security, confidentiality, compliance, data governance, documentation, and supportability.
  • Identify opportunities to improve delivery processes, automate repeatable tasks, reuse data assets, and improve model/report performance.
  • Use approved AI-enabled and productivity tools responsibly to accelerate documentation, testing, analysis, and troubleshooting while validating outputs and protecting client/company data.
  • Provide guidance to Analysts on assigned tasks, technical approach, documentation quality, testing discipline, and Power BI/data engineering fundamentals.
  • Contribute to knowledge-sharing sessions, reusable templates, technical notes, and internal best practices.
  • Work effectively across global teams, time zones, and virtual delivery environments.
  • Perform other projects and tasks as assigned.

Preferred Qualifications

  • Bachelor’s degree in engineering, Information Systems, Data Analytics, Business Analytics, or a related field.
  • 2–4 years of relevant experience in data engineering, analytics engineering, business intelligence, Power BI development, reporting, or software/data platform delivery.
  • Hands-on experience with SQL, Python, ETL/ELT development, data mapping, data validation, and data modeling.
  • Experience working with data warehouses, data lakes, Lakehouse platforms, or analytical database engines such as Databricks, Snowflake, Redshift, SQL Server, PostgreSQL, or similar platforms.
  • Experience developing Power BI dashboards, reports, semantic models, DAX measures, data transformations, and visualization solutions.
  • Ability to understand complex business requirements and translate them into technical designs, data models, dashboards, and tested analytics deliverables.
  • Working knowledge of dimensional modeling, normalization, reporting grain, relationship design, and performance-aware Power BI modeling.
  • Exposure to cloud data services such as Azure Data Factory, Azure storage/containers, AWS S3, AWS Glue, Lambda, Athena, Redshift, RDS, or comparable services.
  • Experience with Git, Azure DevOps, CI/CD workflows, sprint delivery, pull requests, and structured release processes.
  • Strong troubleshooting skills across data pipelines, Databricks notebooks, SQL logic, Power BI refreshes, DAX calculations, access issues, and report performance.
  • Ability to create clear technical documentation, user-facing notes, test evidence, and operational support procedures.
  • Demonstrated ability to work independently with limited supervision while escalating risks and blockers appropriately.
  • Strong communication skills with the ability to explain technical issues to both technical and non-technical audiences.
  • Successful experience working with global teams across multiple geographies and time zones.
  • Strong interpersonal, collaboration, analytical thinking, and teamwork skills.

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