Data Visualization Developer Jobs
Data Visualization Developer jobs are open across finance, healthcare, technology, and media, at every level from entry-level to principal, with specializations in dashboard engineering, data storytelling, and BI tool development. See the openings below and apply to the ones that match your experience.
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About Us
The Freeman Company is a global leader in events, on a mission to redefine live for a new era. With a data-driven approach and the industry’s largest network of experts, The Freeman Company's insights shape exhibitions, exhibits, and events that drive audiences to action. The integrated full-service solutions leverage a 99-year legacy in event management as well as new technologies to deliver moments that matter.
Summary
The Enterprise Data Analytics team is the central source of truth for performance reporting across Sales, Finance, Operations, and Customer Experience (CX). We're looking for a Power BI / AI Visualization Developer who can turn fragmented, multi-source data into clear, trusted dashboards used across the business — and who is ready to push our reporting stack beyond static dashboards into AI-assisted and AI-generated visualization tools.
This role sits at the intersection of BI development, data engineering fluency, and applied AI. You'll build and maintain the enterprise's core Power BI reporting layer, define KPI and data governance standards across functions, and lead the build-out of AI-powered analytics tools — including productionalizing AI-driven dashboards and automation that read directly from our Snowflake warehouse.
This position will support our Technology Services team. It is eligible to work a hybrid schedule, generally requiring work in-office and/or show-site 2-3 days per week. The ideal candidate will be located in Dallas, TX.
Essential Duties & Responsibilities
- Design, build, and maintain Power BI dashboards and semantic models that serve Sales, Finance, Operations, and CX stakeholders with a single, consistent view of performance.
- Enable self-service analytics for business users, and use embedded analytics and data-driven alerts where they get insight in front of stakeholders faster than a dashboard visit.
- Lead the rebuild of existing schemas, semantic models, and Power BI reports currently served from Azure data views onto Snowflake, as part of the team's migration off Azure — re-mapping data models and validating that rebuilt reports match legacy output before cutover.
- Meet with stakeholders to understand the actual business question before building — translating loosely defined asks into clear requirements, rather than jumping straight to a dashboard.
- Establish and enforce KPI definitions, data governance, and QA standards so metrics are calculated consistently across teams and brands/business units.
- Create and maintain documentation for data sources, semantic models, KPI definitions, and Power BI solutions, so institutional knowledge does not live in one person’s head.
- Write and optimize SQL against a Snowflake (or similar cloud warehouse) environment, building views and data models that feed BI tools cleanly and efficiently.
- Optimize the performance and efficiency of Power BI reports, queries, and semantic models — model design, DAX tuning, and incremental refresh — so large models stay responsive as data volumes grow.
- Design and productionalize AI-assisted or AI-generated reporting tools — for example, LLM-powered summarization of dashboard results, natural-language query layers over Snowflake data, or automated deck/report generation — moving them from prototype to a reliable, team-wide production tool.
- Audit and validate dashboard and data model inputs by hand when outputs look off, tracing discrepancies back to source data or logic errors rather than taking vendor or pipeline outputs at face value.
- Build lightweight internal tools (e.g., Python/Streamlit apps) that automate recurring, manual reporting cycles and cut turnaround time for the team.
- Own recurring reporting cadences (weekly/monthly, quarterly business reviews) with a consistent, repeatable production process.
- Evaluate new data sources and analysis methods, recommending the right approach for the right decision (e.g., trend/diagnostic reporting vs. deeper analysis).
- Help administer the Power BI environment — workspace and report access, row-level security (RLS) so users see only the data appropriate to their role, and gateway/data source connections and refresh schedules — working alongside the current workspace admin.
- Mentor junior analysts on Power BI, SQL, and data hygiene best practices as the team grows.
Education & Experience
- Bachelor's degree in a quantitative, business, or technical field (e.g., Analytics, Statistics, Business, Computer Science) or equivalent practical experience.
- 5- 8 years of experience in analytics, business intelligence, or a related data role, including hands-on BI development.
- Strong Power BI skills: data modeling, DAX, Power Query/M, and report/dashboard design.
- Strong SQL skills and experience working against a cloud data warehouse (Snowflake, BigQuery, Redshift, or similar).
- Demonstrated experience turning multi-source, messy, or inconsistent data into a single reliable reporting layer.
- Strong communication skills — able to listen closely, ask the right clarifying questions, and clearly explain technical work to non-technical stakeholders before and after building a solution.
- Experience migrating BI reporting from one cloud data warehouse to another (e.g., Azure to Snowflake), including rebuilding data models and validating parity with legacy reports.
- Exposure to administering Power BI at an enterprise level — workspace/access management, row-level security (RLS), gateways, and refresh scheduling — is a plus.
- Experience keeping semantic models under source control and deploying them through a repeatable process (Git integration, TMDL, deployment pipelines).
- Familiarity with the external tooling ecosystem for semantic models — Tabular Editor, DAX Studio, ALM Toolkit, and Best Practice Analyzer.
- Direct experience productionalizing an AI-based dashboard or reporting tool that reads from Snowflake (or a comparable warehouse) — e.g., an LLM-powered insights layer, natural-language-to-SQL interface, automated narrative/report generation, or similar — taken from prototype to a stable tool used by a team.
- Experience building automation or internal tools with Python (e.g., Streamlit, or similar lightweight app frameworks).
- Experience setting or governing measurement/attribution or KPI standards across multiple teams or business units.
- Some exposure to ETL/data pipeline work (e.g., Stitch, Fivetran, dbt, or custom pipelines) in addition to reporting.
Travel Requirements
What We Offer
The Freeman Company provides benefits that aim to empower our people and their families to thrive mentally, physically, and financially. These are a handful of the types of programs and benefits our full-time people may be eligible for. There may be some variances in specific benefits across regions.
- Medical, Dental, Vision Insurance
- Tuition Reimbursement
- Paid Parental Leave
- Life, Accident and Disability
- Retirement with Company Match
- Paid Time Off
Diversity Commitment
At The Freeman Company, our commitment to diversity and inclusion is helping us to create not only a great place to work, but also an environment where our employees, our customers and our communities around the world can reach their goals and connect with each other. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status and other characteristic protected by federal, state or local laws.
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Data Visualization Developer Jobs by Experience Level
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Who's Hiring



Top Industries Hiring
- Technology & Software
What Employers Look For
The qualifications that appear most often in data visualization developer jobs.
- Proficiency in Tableau, Power BI, or Looker for building production dashboards
- Experience with D3.js or similar JavaScript charting libraries for custom web visualizations
- Strong SQL skills for querying and preparing data from relational databases
- Bachelor's degree in computer science, data science, statistics, or a related field
- Familiarity with Python or R for data manipulation and preprocessing
- Portfolio of published or deployed visualization projects demonstrating design and technical skills
Tips for Your Data Visualization Developer Job Search
Tailor your portfolio for each application
Recruiters for data visualization developer roles scan portfolios before resumes, so swap in samples that match the industry you're targeting. A healthcare analytics dashboard communicates more than a generic bar chart demo when you're applying to a hospital system.
Name your tools explicitly on your resume
Applicant tracking systems filter candidates by tool names, so write out Tableau, Power BI, D3.js, Vega-Altair, or Apache ECharts exactly as they appear in the job posting. Listing only 'data visualization tools' will get your resume filtered out before a human reads it.
Apply early to roles that fit
Migrate Mate lists data visualization developer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Highlight the data pipeline behind your visuals
Many job postings expect you to own the full workflow from raw data to finished chart. Call out your SQL, Python, or dbt experience alongside your front-end charting skills so hiring managers don't assume you only work downstream of a data engineer.
Prepare a live walkthrough for technical screens
Most data visualization developer interviews include a take-home or live coding round where you build or refactor a chart under time pressure. Practice narrating your design decisions out loud, because interviewers evaluate your reasoning about color, hierarchy, and accessibility as much as your code.
Negotiate using performance benchmarks not just titles
When you reach the offer stage, anchor your ask to measurable impact from past work, such as dashboard adoption rates or time-to-insight improvements you delivered. Concrete metrics give you leverage that seniority-level comparisons alone don't.
Data Visualization Developer Jobs: Frequently Asked Questions
Which companies are hiring the most data visualization developers?
The most active employers for data visualization developers right now are SAIC, Freeman, and Akina, and the most openings are in Virginia, Maryland, and Texas, based on current listings on Migrate Mate as of September 2026. Demand is particularly high in industries with large internal analytics teams, such as financial services and enterprise technology.
How many data visualization developer jobs are remote?
About 50% of data visualization developer openings are fully remote or hybrid as of September 2026, reflecting strong demand for distributed analytics talent. Roles focused on front-end charting and BI tool development tend to be the most remote-friendly, while positions embedded in real-time operations or executive reporting often prefer on-site or hybrid arrangements.
How do you become a data visualization developer?
Start by building proficiency in at least one major BI platform such as Tableau or Power BI and one JavaScript charting library such as D3.js. Develop your SQL skills so you can pull and transform data without relying on a separate engineer. Build a portfolio of three to five projects that show both design judgment and technical execution, then target entry-level analyst or junior developer roles that overlap with visualization work to gain professional experience.
Can you get a data visualization developer job with little experience?
Yes, entry-level data visualization developer roles exist, and a strong portfolio can outweigh a thin resume. Focus on building public projects using real datasets, such as government open data or nonprofit reporting, and publish them with documented code. Roles with titles like data analyst, BI analyst, or reporting developer often serve as direct entry points and involve the same core visualization skills.
What does the data visualization developer interview process look like?
Most processes include an initial recruiter screen, a technical phone interview covering SQL and charting tool familiarity, and a take-home or live coding exercise where you build or improve a visualization. A final round typically involves presenting your exercise to a panel and defending your design choices around layout, color accessibility, and data accuracy. Some employers also include a stakeholder role-play to assess how you translate business requirements into a visual specification.
Where can I find and apply to data visualization developer jobs?
You can find and apply to data visualization developer jobs on Migrate Mate, which lists current openings from across the United States. Search for roles that match your tool expertise and seniority level, then apply directly to each listing that fits your background.
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