Analytics Engineer - Analyst

This role is particularly suited to early-career candidates who want exposure to the complete analytics delivery lifecycle rather than working on only one technology. The position combines SQL, Python, Power BI, data modeling, cloud and Databricks exposure, testing, documentation, and stakeholder collaboration.

🔍 What You’ll Work On

The Analytics Engineer - Analyst will support the development and maintenance of data and analytics solutions used across Huron. The work can involve data pipelines, datasets, semantic models, dashboards, and reports.

You will assist senior team members with extracting data from different sources, transforming it into usable formats, loading datasets, validating results, and reconciling information against source systems. Attention to detail is important because the role involves checking whether reports and datasets accurately represent the underlying business data.

The position also includes supporting report development and helping troubleshoot issues related to data refreshes, visualizations, access, data quality, and report performance.

🛠 Technical Environment

The role provides exposure to a combination of analytics, database, cloud, and business intelligence technologies.

Core technologies mentioned for the position include:

SQL Python Power BI DAX Databricks

Candidates may also encounter technologies and platforms such as Azure Data Factory, AWS S3, AWS Glue, Redshift, Snowflake, Git, Azure DevOps, and JIRA depending on project requirements.

A candidate does not need to be an expert across every platform listed. The position is designed for entry-level to early-career professionals, with development taking place under the guidance of experienced team members.

📈 Power BI & Data Modeling

Power BI is an important part of this position. Candidates will support the development of reports and dashboards using approved design standards, visuals, slicers, filters, and basic DAX calculations.

You will also work with Power BI semantic models, which requires understanding how source tables connect to one another and how relationships, joins, business grain, dimensions, and measures affect reporting.

For example, if a sales report contains customer, product, transaction, and date information, you should understand how these tables relate and how those relationships influence the numbers displayed in a Power BI dashboard.

🧩 ETL, Data Quality & Validation

The position involves supporting ETL and ELT activities throughout the analytics delivery process.

Responsibilities can include data extraction, transformation, loading, mapping, reconciliation, and validation. You will also participate in testing activities where report results and datasets are compared against expected values or source information.

Data quality is a significant part of the role. Candidates should be comfortable investigating mismatched values, missing records, unexpected results, and other inconsistencies before analytics outputs are shared with stakeholders.

Strong attention to data validation is expected.

🐍 SQL & Python Responsibilities

Candidates should have foundational SQL knowledge and be comfortable writing basic to intermediate queries.

SQL may be used for data preparation, analysis, validation, reconciliation, and reporting requirements. Understanding relational databases, joins, filtering, aggregations, and data relationships will be useful for day-to-day work.

Python will support data preparation, automation, validation, and analytical tasks. The role does not require advanced software engineering experience, but candidates should understand Python fundamentals and be able to create practical scripts when required.

🧪 Testing & Production Support

Testing is an important part of the analytics delivery lifecycle at Huron. The analyst will support unit testing, report validation, data comparison, UAT activities, defect documentation, and issue remediation.

You may also help investigate basic production issues involving data refreshes, dashboard visuals, access permissions, data quality, or report performance. More complex issues are expected to be escalated to senior team members.

This makes the position useful for candidates who want to understand how analytics solutions move from development into real business use.

🤝 Team & Stakeholder Collaboration

The role involves collaboration with Data Engineers, Power BI Developers, Data Architects, QA teams, team leads, business stakeholders, and project teams across the United States and India.

You may participate in requirements discussions, sprint ceremonies, status meetings, knowledge-sharing sessions, and issue-resolution activities. Clear communication is important because analysts need to document reporting requirements, data definitions, assumptions, open questions, technical notes, and testing results.

The position also requires candidates to communicate blockers early and follow through on assigned tasks.

🎓 Who Can Apply

The preferred educational background includes a bachelor's degree in:

• Engineering

• Information Systems

• Data Analytics

• Business Analytics

• A related technical or analytical field

Huron is looking for candidates with 0–2 years of experience in areas such as data engineering, analytics, business intelligence, reporting, software development, or related project work.

Fresh graduates with relevant coursework, projects, internships, or practical exposure to SQL, Python, Power BI, and data analytics can align well with the entry-level nature of the role.

📚 Skills Worth Building

Candidates preparing for this type of position should focus on practical rather than purely theoretical knowledge.

Important areas include:

SQL: joins, aggregations, filtering, subqueries, data validation, and relational database concepts.

Python: fundamentals, data manipulation, scripting, and automation.

Power BI: report creation, visuals, filters, relationships, semantic models, and introductory DAX.

Data Engineering: ETL/ELT concepts, data pipelines, data warehouses, data lakes, and Lakehouse fundamentals.

Cloud & Analytics Platforms: basic familiarity with Databricks and platforms such as Azure or AWS can strengthen a candidate's profile.

Development Workflow: Git, Azure DevOps, JIRA, testing, documentation, and issue tracking.

🌐 Global Work Environment

The Bangalore team will collaborate with colleagues and stakeholders across India and the United States. Candidates should be comfortable working in a team-oriented environment involving different functions, time zones, and project requirements.

The role is hybrid, giving candidates exposure to both collaborative workplace interactions and structured project delivery.

🎯 What Recruiters May Evaluate

Candidates may be assessed on their ability to understand data, write SQL queries, explain relationships between tables, work with reporting requirements, identify data inconsistencies, and communicate technical findings clearly.

Practical understanding of Power BI, Python, data modeling, ETL/ELT, and testing can strengthen a candidate's profile.

For freshers, academic projects involving dashboards, databases, ETL pipelines, analytics, or Python automation can provide useful evidence of hands-on capability.

🔑 Keywords for Resume

SQL • Python • Power BI • DAX • Data Analytics • Data Engineering • ETL • ELT • Data Modeling • Semantic Modeling • Databricks • Data Warehousing • Data Lakes • Lakehouse • Azure Data Factory • AWS S3 • AWS Glue • Snowflake • Redshift • Git • Azure DevOps • JIRA • Data Validation • Data Quality • Dashboard Development • Business Intelligence • Reporting • UAT • Data Pipelines

💡 Final Perspective

The Huron Analytics Engineer - Analyst position provides entry-level exposure across data engineering, business intelligence, reporting, and analytics delivery. It is a suitable opportunity for candidates who want to develop practical experience with SQL, Python, Power BI, data modeling, ETL/ELT, testing, and enterprise analytics platforms while working with global project teams.