Senior Power BI Developer

We're a data and analytics team that builds reporting products for enterprise clients. We need a Power BI developer who can pick up a complex existing model, figure out what's wrong with it, and fix it — then keep building on top of it.

This isn't a role where you'll be handed clean requirements and told what to build. You'll be given a problem, access to the data, and expected to drive to a solution. If that sounds like your normal working style, keep reading.

• Start - As soon as possible
• Stack - Cloud data warehouse → Power BI Import Mode
• Model size - Large enterprise model — 80+ tables, 200+ DAX measures
• Shift Time - IST 3pm to 12am 

Day to day, the work looks like this:

• Taking ownership of reports that are already in production — diagnosing performance issues, fixing broken measures, and extending them with new pages and features
• Writing DAX from scratch. Not adjusting templates or copying patterns from documentation — actually understanding what the engine is doing and writing accordingly
• Working directly with stakeholders who don't speak Power BI. You'll need to ask the right questions to understand what they actually need, not just what they're asking for
• Keeping the data model clean — removing dead weight, managing relationships, and making sure things don't fall apart when the data changes upstream
• Collaborating with data engineers when a problem traces back to the source — you don't need to be a SQL expert, but you need to be able to have a technical conversation

Hard requirements — don't apply if you can't tick all of these:

• 5+ years of Power BI development on real enterprise models, not demos or training datasets
• DAX at an expert level. CALCULATE, SUMX, TREATAS, FILTER, GROUPBY, time intelligence — you know when to use each one and why, and you can debug your own work
• You know how to use DAX Studio — not just open it, but actually use Server Timings to figure out where a slow query is spending its time
• Tabular Editor is part of your normal workflow, not something you Google when someone mentions it
• Power Query (M) — you can write and fix transformation steps without clicking through the GUI
• You understand the data model underneath the visuals: relationship direction, cardinality, filter propagation, and what breaks when you get these wrong
• SQL — enough to read a query, write a basic one, and hold a conversation with an engineer about what's happening in the database

We expect hands-on familiarity with these. We'll ask about them in the interview:

• DAX Studio - Query diagnosis, Server Timings, VertiPaq Analyzer — the main tool for any serious performance work
• Tabular Editor 2 or 3 - Best Practice Analyzer, batch measure editing, model cleanup
• Performance Analyzer - Identifying which visuals and queries are slow, built into Power BI Desktop
• Measure Killer - Finding and removing unused measures and columns from the model
• Bravo for Power BI - DAX formatting and model documentation
• ALM Toolkit - Comparing and deploying model schema changes across environments
• Optimize Ribbon - Pausing visuals while editing, managing aggregations

Good to have :

• Background in real estate, energy, or sustainability data — we work in this space, so familiarity helps
• Experience with Power BI Service — workspaces, refresh schedules, deployment pipelines, RLS
• Incremental refresh and large fact table strategies

Probably not a fit if...

• You need requirements fully written before you can start
• You fix performance by cutting data, not by fixing the DAX
• You use AI tools to write your measures
• Your models work but nobody else can maintain them

Likely a strong fit if...

• You're comfortable working backwards from a business problem
• Your first step with a slow report is Performance Analyzer and DAX Studio
• You write DAX from memory and can explain every line
• You write clean, commented code like someone else will need to read it

Send us two things:

• Your CV — focus on the Power BI projects, not the job titles. Tell us the model size, what the data looked like, and what you specifically built or fixed
• One real example of a performance problem you diagnosed and solved in Power BI. Show the before and after, and explain what was actually wrong. A paragraph is fine — we don't need a case study

We read every application. If you don't include the performance example, we'll assume you don't have one.