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.
- Position Level
- Senior Analyst
