BI developer with 9 years of experience designing data warehouses, ETL and enterprise reporting on the Microsoft stack. Migrated an on-premises SSAS environment to Azure and Power BI, cutting reporting costs 35%. Writes performant SQL and DAX and builds semantic models business teams can trust.
Experience
BI Developer, Silverpine Manufacturing (Grand Rapids, MI)
Sep 2021 – Present
Migrated on-premises SSAS cubes and 150 SSRS reports to Azure Synapse and Power BI, cutting reporting infrastructure costs 35%
Built Azure Data Factory pipelines loading ERP and MES data nightly with 99.7% on-time success
Designed shared Power BI semantic models with incremental refresh serving 500 users
Tuned SQL and DAX measures, reducing slowest report load from 90 seconds to 9
SQL and Reporting Developer, Great Lakes Auto Parts (Detroit, MI)
Jan 2019 – Aug 2021
Developed SSIS packages integrating 6 source systems into a Kimball-style warehouse
Built 60 SSRS reports for sales, purchasing and quality teams
Tuned warehouse indexes, cutting nightly ETL runtime from 5 hours to 2
Junior Database Developer, Huron Data Services (Ann Arbor, MI)
Jun 2017 – Dec 2018
Wrote T-SQL stored procedures for client reporting databases
Education
B.S. in Computer Science, Michigan State University (Aug 2013 – May 2017)
Skills
Microsoft BI: Power BI, DAX, SSAS Tabular, SSRS, SSIS
Cloud Data: Azure Synapse, Azure Data Factory, Azure SQL
Certifications: Microsoft Certified: Fabric Analytics Engineer Associate (DP-600)
How to write a BI Developer resume
A strong BI Developer resume shows the questions you answered, the models or pipelines you shipped, and the decisions your analysis changed. Put your most relevant recent role first and make every bullet show a result, not a duty.
Sections, in order
Summary
Experience
Projects
Skills
Education
Length: One page for most candidates; move to two only if every line is relevant.
Summary: Write two or three lines: your role, your strongest skills, and one result that proves them.
Skills to feature
SQL
Python or R
Statistics
Machine learning
Data modeling
dbt and ELT pipelines
BI tools (Looker, Tableau, Power BI)
Experiment design
Data visualization
Stakeholder communication
Example bullet points
Built a churn model (gradient boosting, AUC 0.86) that targeted retention offers and saved $900k a year
Rebuilt the revenue dashboard on dbt and Looker, cutting refresh time from 6 hours to 20 minutes
Designed 25 A/B tests with sequential analysis, shortening the average test from 4 weeks to 10 days
Tips from recruiters
Pair every technique with the decision it informed; "built a model" alone says little.
List tools under grouped skills ("Analytics: SQL, dbt, Looker") so ATS keyword matches are exact.
Link a notebook, Kaggle profile or public analysis if you have one.
Recommended templates
Classic (ATS-friendly): Jake's-style LaTeX classic: small caps and hairline rules
Modern (ATS-friendly): Clean single column with accent headings and rules
Compact (ATS-friendly): Dense single column that fits long histories
BI Developer resume FAQ
What should a BI Developer resume include?
A BI Developer resume should show the questions you answered, the models or pipelines you shipped, and the decisions your analysis changed. Use these sections in this order: Summary, Experience, Projects, Skills and Education. Put your most relevant recent role first and make every bullet show a result, not a duty.
What is the best resume template for a BI Developer?
Classic, Modern and Compact work well for BI Developer roles. They are single-column with standard headings, so applicant tracking systems (ATS) parse them reliably.
How long should a BI Developer resume be?
One page for most candidates; move to two only if every line is relevant.
Which skills should a BI Developer put on a resume?
Prioritize the skills named in the job posting. Common ones for BI Developer roles are SQL, Python or R, Statistics, Machine learning, Data modeling and dbt and ELT pipelines.
How do I write strong BI Developer resume bullet points?
Start with an action verb, say what you did, and end with a measurable result such as forecast accuracy, revenue impact and query time. For example: "Built a churn model (gradient boosting, AUC 0.86) that targeted retention offers and saved $900k a year."