Analytics Engineer

About the role

Roles and Responsibilities

• Design, develop, maintain, and enhance semantic models and BI solutions
• Build and enhance Power BI and SSAS/AAS models, including measures, relationships, calculations, and business logic
• Translate business requirements into data models, semantic layer solutions, and BI enhancements
• Analyze data using SQL and other tools to identify data quality issues, inconsistencies, and trends Perform data validation and reconciliation across different data layers
• Troubleshoot and resolve issues related to reports, datasets, semantic models, cubes, data refreshes, and underlying data
• Investigate issues across Snowflake/Databricks, ETL pipelines, ADF, and the BI/semantic layer to determine root cause
• Partner with Data Engineering and other technical teams to resolve complex data and pipeline issues
• Perform root-cause analysis and implement sustainable solutions to prevent recurring production issues
• Monitor and improve the performance, reliability, and scalability of BI and semantic models
• Participate in development activities including new functionality, enhancements, model changes, and technical improvements
• Support production BI solutions while continuously identifying opportunities to improve data quality, performance, automation, and maintainability
• Work closely with business stakeholders to understand reporting requirements and ensure business definitions and KPIs are accurately represented in the semantic layer
• Contribute to BI/Analytics Engineering standards, best practices, and architecture discussions
• Qualifications and experience
• Bachelor’s degree required, preferably with a quantitative focus (Statistics, Business Analytics, Data Science, Math, Economics, etc.)
• Master’s degree preferred (MBA/MS Computer Science/M.Tech Computer Science, etc.)
• 3+ years of experience in Analytics Engineering, BI Development, BI Production Support, or a similar role

Preferred Skills

• Strong hands-on experience with Power BI and SSAS/Azure Analysis Services (AAS)
• Experience developing and maintaining semantic models / analytical models
• Strong SQL skills with the ability to analyze complex data and perform data validation
• Good understanding of dimensional data modeling, business logic, measures, KPIs, relationships, and calculations
• Experience troubleshooting Power BI reports, datasets, semantic models, cubes, and data refresh issues
• Experience with Snowflake and/or Databricks
• Good understanding of ETL/data pipelines and Azure Data Factory (ADF)
• Ability to trace data issues across source, data warehouse, refined/curated layers, and semantic models
• Experience with data quality validation, reconciliation, and root-cause analysis
• Understanding of BI and semantic model performance optimization
• Experience working with incident management and production issues, including investigation, resolution, and prevention of recurring issues
• Ability to collaborate with Data Engineering, Data Architecture, QA, and business teams
• Strong analytical and problem-solving skills with the ability to investigate issues independently
• Strong communication skills and ability to work directly with business users and technical stakeholders
• Behavioral Skills
• Delivery Excellence
• Business disposition
• Social intelligence
• Innovation and agility
• #LI-DS1 #LI-SS3