BI Analytics Engineer

We are seeking a BI / Analytics Engineer to support the data, semantic model, and reporting components of contact center analytics solutions built on Microsoft Fabric and Power BI.

This role is responsible for transforming curated data into trusted, reusable analytical models and for the day-to-day sustainment and enhancement of a centralized Power BI semantic model supporting multiple business reports. The successful candidate will work directly with Gold Lakehouse tables, Direct Lake semantic models, DAX measures, relationships, metadata, and downstream Power BI reports to ensure reporting data is accurate, consistent, performant, and supportable.

The role will investigate production incidents and data discrepancies across the analytical reporting path, from curated Fabric data through the semantic model and report layer. It will implement semantic model changes, reusable metrics, minor upstream transformations where appropriate, report enhancements, and new reports for business users. The role works closely with data engineers, business subject matter experts, and technical support teams, but remains a hands-on technical delivery position.

• Maintain and enhance centralized Power BI semantic models used by multiple downstream reports.
• Design and manage fact and dimension tables, relationships, hierarchies, perspectives, display folders, formatting, metadata, and model organization.
• Develop, test, document, and optimize reusable DAX measures and shared KPI logic.
• Assess downstream impacts before changing tables, columns, relationships, measures, or calculation logic.
• Maintain consistent metric definitions and business rules across reports connected to the shared model.
• Identify unused or duplicative model objects and support controlled model cleanup.
• Use model lineage and dependency analysis to understand how semantic model changes affect reports and calculations.

• Support semantic models operating in Direct Lake mode against Fabric Lakehouse Delta tables.
• Troubleshoot Direct Lake issues involving data availability, framing, model metadata, table or column changes, relationships, partitions, and report query behaviour.
• Validate that non-production and production Lakehouse schemas remain compatible with semantic model deployments.
• Work with Fabric Lake houses, SQL analytics endpoints, notebooks, deployment pipelines, work spaces, and Power BI Apps as required for reporting delivery.
• Distinguish between source-data freshness, pipeline completion, semantic model state, and report-layer behaviour during incident investigation.
• Participate in performance analysis involving table size, cardinality, query patterns, DAX complexity, concurrency, and Fabric capacity consumption.
• Analyze curated data to understand grain, keys, relationships, duplicates, nulls, late-arriving records, and source-system exceptions.
• Validate fact and dimension data across Fabric Lakehouse tables, the semantic model, DAX query results, and Power BI report outputs.
• Reconcile business metrics against source-system or operational results and explain confirmed differences.
• Determine whether reported issues originate in source data, Silver-to-Gold transformation logic, the semantic model, DAX, filters, or report configuration.
• Write SQL, DAX queries, and notebook-based validation code to investigate incidents and verify changes.
• Partner with data engineers when fixes require changes to Gold tables, aggregation tables, notebooks, or upstream transformation logic.

• Respond to P2-P4 IT incidents and user-reported issues related to data, semantic models, Power BI reports, calculations, performance, and missing or incomplete results.
• Perform structured root cause analysis and document evidence, findings, resolution, workarounds, and escalation paths.
• Reproduce issues using defined filters and time periods, validate expected logic, and confirm the resolution with business users.
• Escalate source-system, pipeline, platform, access, or capacity issues to the appropriate technical team with clear diagnostic evidence.
• Maintain technical runbooks, known-issue documentation, model documentation, and incident investigation procedures.

• Develop and maintain Power BI reports that consume the centralized semantic model.
• Implement new measures, filters, visuals, drill-through paths, tooltips, report pages, and usability improvements.
• Build new reports using shared,…