Job Description

Senior Power BI Developer

Modelling. Analytics. AI & Automation. Power Platform

Experience: 6-8 Years

Role Overview

We are hiring a Senior Power BI Developer who can deliver on health, evolution, and quality of our reporting and automation layer — from the semantic model and DAX logic through to the Power Platform integrations, AI-driven insights, and agentic workflows that business stakeholders rely on daily.

The person is expected to bring depth across data modelling, advanced DAX, SQL, Power Query, visualisation design, and the full Power Platform stack — Power Automate for pipeline orchestration and intelligent alerting, Power Apps for operational data capture and writeback, Copilot Studio for conversational BI agents, and AI Builder for document intelligence and predictive enrichment. A meaningful part of the role involves revamping legacy reports, building net-new analytical products, and designing agentic automation that closes the loop between insight and action.

Key Responsibilities

Power BI — Modelling, Reports & Performance

Own the day-to-day health of Power BI datasets — scheduled refresh monitoring, gateway management, RLS validation, incremental refresh partition health, and downstream consumer impact assessment.
Design and build new reports end to end — from understanding the business ask and shaping the data model, through DAX measure authoring and visual design, to RLS setup, deployment, and UAT sign-off — without disrupting existing datasets or shared semantic layers.
Revamp legacy reports — assess existing design against current standards, identify performance bottlenecks, redesign the model where needed, and re-deliver with improved UX, cleaner DAX, AI-assisted narrative, and measurably better stakeholder adoption.
Maintain and evolve semantic models — star schema design, role-playing dimensions, many-to-many bridge tables, composite models (Import + DirectQuery), aggregation tables, and hybrid tables for large dataset performance.
Configure and manage incremental refresh end to end — RangeStart/RangeEnd parameters, partition windows, hybrid table setup, and partition stability across model changes.
Profile and optimise slow reports and models using DAX Studio Server Timings and Performance Analyser — reduce Formula Engine load, right-size VertiPaq models, and design aggregation tables over DirectQuery sources.
Write efficient, production-grade SQL for upstream views, aggregation tables, validation checks, and analytical extracts. Optimise slow queries and identify data layer bottlenecks before they surface in the report.

Advanced Visualisation & Data Storytelling

Apply data storytelling principles to every report — clear narrative arc (what happened, why it happened, what to do), executive vs operational layout distinction, and visual hierarchy that communicates the key message within three seconds of page load.
Use F-pattern layout, purposeful colour encoding, white space discipline, and conditional formatting driven by DAX measures — not hard-coded thresholds.
Build dynamic, self-service reports using field parameters, bookmark-driven tab navigation, drill-through, tooltip pages, and DAX-driven dynamic commentary that updates with every filter selection.
Design executive summary pages (5 KPIs, one trend, one comparison — nothing else) and operational detail pages (filterable matrices, drill-through, export) as distinct, audience-specific products.
Use colour to encode meaning — traffic-light measures, diverging scales with meaningful midpoints, and accessible palettes that work without colour distinction alone.

AI-Powered Visualisation & Intelligent Insights

Integrate Power BI native AI visuals into reports — Anomaly Detection on time-series trends, Smart Narratives with customised DAX-enhanced commentary, Key Influencers for driver analysis, and Decomposition Trees for self-service root cause exploration.
Configure and govern the Q&A visual — build synonyms, define featured questions, train the linguistic schema so business users can query the model in natural language without hitting incorrect results.
Extend AI capabilities beyond native visuals — integrate Azure OpenAI, Azure Cognitive Services, or Azure Machine Learning outputs into Power BI via Power Query or dataflows: sentiment scoring on operational text, classification labels, forecast enrichment, and anomaly flags surfaced as model columns that visuals consume.
Use Copilot for Power BI (where available) for accelerated report generation, DAX measure suggestions, and narrative summarisation — while maintaining governance over AI-generated outputs before they reach business consumers.
Build AI-enriched data pipelines in Dataflow Gen2 / Microsoft Fabric where AI transformation steps (OCR, entity extraction, prediction) are centralised and reusable across multiple downstream reports.

Power Automate — Orchestration, Alerts & Agentic Flows

Build Power Automate flows connected to Power BI — data-driven alerts triggered on KPI threshold breaches, automated report distribution via email and Teams, refresh failure notifications with RCA context, and approval workflows that act on BI-surfaced exceptions.
Design multi-step orchestration flows across Microsoft 365, Dataverse, SharePoint, and external APIs — handling conditions, error branches, parallel actions, and retry logic for production-grade reliability.
Build agentic automation flows that respond to data events without human trigger — scheduled anomaly sweeps that detect, classify, and route exceptions to the right team; flows that aggregate multi-source data, generate a narrative summary via Azure OpenAI, and push it to a Teams channel or email digest automatically.
Integrate Power Automate with Power BI REST API — automate dataset refresh triggers, workspace provisioning, report export to PDF/email on schedule, and access audit log extraction for governance reporting.
Use AI Builder within Power Automate — document processing (invoices, contracts, trade confirmations), prediction model scoring, form recognition, and text classification — feeding structured outputs back into Dataverse or SharePoint for downstream Power BI consumption.
Govern and document flows — naming conventions, solution-based deployment, environment strategy (Dev/Test/Prod via Power Platform pipelines), and connection ownership to prevent orphaned flows.

Power Apps — Operational Tools, Writeback & Embedded BI

Design and build canvas apps for data entry and writeback — forms that capture operational data into SharePoint or Dataverse, close the loop on BI-surfaced exceptions, and feed structured inputs back into the reporting layer.
Embed Power Apps within Power BI reports for in-context actioning — a user sees an exception in a visual, clicks into an embedded app panel, enters a resolution or annotation, and the action is written back without leaving the report.
Build AI-integrated canvas apps — apps that use AI Builder models (document scanner, prediction, object detection) to process user inputs and feed enriched, structured data into Dataverse or SharePoint for downstream BI consumption.
Design power apps where structured data management, business rules, and process automation matter more than custom UI — connected to Dataverse tables that Power BI reports query directly.

Copilot Studio — Conversational BI Agents & Data Assistants

Build and configure Copilot Studio agents that give business users a conversational interface to BI data — natural language queries answered from Power BI datasets, Dataverse tables, or SharePoint knowledge bases, without writing DAX or SQL.
Design topic flows, entity extraction, and adaptive cards within Copilot Studio — structured responses with embedded charts, KPI summaries, and drill-down links returned as part of the conversation.
Connect agents to Power Automate flows as actions — a user asks the agent a question, the agent triggers a flow, the flow queries live data or executes a business process, and the result is surfaced back in the conversation.
Integrate agents with Azure OpenAI via Generative Answers — grounding responses in internal knowledge (report documentation, data dictionaries, process guides) so the agent answers accurately from your data, not from general model knowledge.
Govern agent behaviour — define fallback topics, escalation paths, usage analytics via Copilot Studio dashboards, and content moderation guardrails to prevent hallucinated or out-of-scope responses reaching business users.

Governance, Deployment & Platform Engineering

Manage Power BI Deployment Pipelines (Dev → Test → Prod) — deployment rules, parameter substitution, gateway binding, and post-deploy validation. Mirror with Power Platform pipelines for coordinated release of apps, flows, and reports.
Work with Git-integrated PBIP format — branch-based development, readable DAX diffs in pull requests, and conflict resolution on model changes.
Design workspace and environment strategy aligned to domains, not individual reports — govern via Apps, dataset endorsement (Promoted/Certified), and certified semantic model promotion to shared consumers.
Maintain report documentation, data dictionaries, measure descriptions, and lineage records using Tabular Editor or equivalent — governance artefacts are part of the delivery, not an afterthought.
Build and maintain a testing layer — DAX output validation against source SQL, RLS role testing, Power Automate flow testing, AI output quality checks, and visual regression suites — so every release goes out with confidence.
Mentor junior developers — review data models, DAX measures, Power Query scripts, Power Automate flows, and app designs for quality, performance, and standards compliance.