×
LakeFusion
AI-powered Master Data Management platform built natively on Databricks
Last verified August 17, 2026 · Updated daily
What LakeFusion is building
LakeFusion is not a new data product bolted onto Databricks. It is MDM rebuilt from scratch inside the lakehouse so data never has to leave. Enterprises point the platform at the tables they want to clean, and LakeFusion runs AI-driven entity resolution and deduplication to produce golden records: single, trusted, governed master records for customers, products, suppliers, patients, properties, or any other critical domain. The rules engine, the governance layer, the survivorship logic, and the real-time sync back to CRM and ERP all run natively inside Databricks, which means no ETL pipeline, no separate MDM infrastructure, and no data movement. Install it from the Azure or AWS Marketplace, point it at your tables, and go. The platform balances LLMs with a broader suite of matching and deduplication techniques to stay cost-effective at enterprise scale.
Why this matters
Enterprise AI is stalling not because models are bad but because the data underneath them is broken. A GPT-4-level model trained on a customer database with 40% duplicate records produces confident nonsense. MDM, the discipline of creating single authoritative records across systems, has been the unglamorous fix for this problem for thirty years. The legacy players, Informatica, Reltio, Semarchy, are architecturally designed for a pre-lakehouse world: expensive, slow to deploy, and built around moving data into a separate MDM system. That architecture made sense in 2005. It makes no sense in 2026, when most enterprise data already lives in Databricks. Silverton Partners GP Mike Dodd said it precisely in the announcement: "As enterprise AI moves into production, the bottleneck is no longer model capability, it's data fidelity." LakeFusion's moat is the Databricks-native architecture. No other MDM platform is built this way. The Databricks ISV Partnership and dual Marketplace listings validate the technical approach from the ecosystem itself.
Open roles at LakeFusion
11 positions we're tracking. Roles are re-checked daily and removed when filled.
Principal Backend Engineer
First seen 3 months ago
PIM Engineering Lead
First seen 3 months ago
Senior MDM Architect
First seen 3 months ago
Data Engineer
First seen 3 months ago
Integration Engineer
First seen 3 months ago
GCP & Platform Security Engineer
First seen 3 months ago
Full Stack Engineer
First seen 3 months ago
AI/ML Engineer
First seen 3 months ago
Level 2 Technical Support Engineer
First seen 3 months ago
Level 1 Customer Support Engineer
First seen 3 months ago
QA Engineer
First seen 3 months ago
Know when LakeFusion is hiring before anyone else
A role stays uncontested for about four days. Here's the window — and where we put you in it.
From $9/month, cancel any time.
Watching LakeFusion
0 applicantsRole spotted & verified
1You get the alert
1You've applied
~8Hits the job boards
250+Hiring outlook
Very High. Press release explicitly states the round will grow engineering and go-to-market teams. Nine remote roles live on the careers page today, all requiring direct email to careers@lakefusion.ai. No ATS bloat, no recruiter layer.
Working at LakeFusion
LakeFusion is AI-powered Master Data Management platform built natively on Databricks, founded in and now <50 people. At this stage, expect broad remit, direct access to founders, and equity that still means something if the company works out.
Austin is where most LakeFusion positions are located.
How to actually get hired at LakeFusion
Why applying the normal way doesn't work
At this size (<50 people), LakeFusion has no recruiting function. Founders handle hiring alongside everything else. Reach them directly or get lost in the inbox.
Who to contact at LakeFusion
Founding team
Vikas Punna spent roughly two decades building, running, and eventually selling a data management consulting firm before founding LakeFusion, which means he is not a first-time founder learning the enterprise data market on the job. He founded UNICO Solutions, a data strategy and technology consulting firm where he was Managing Partner and VP of Data Management, specializing in Informatica's data integration suite, data quality, governance, and ERP and CRM services. Huron Consulting Group acquired UNICO in 2021, bringing more than 30 of UNICO's global workforce into Huron. Vikas became Managing Director of Data Management and Analytics at Huron, one of the most respected healthcare and higher education consulting firms in the US, where he stayed until the LakeFusion opportunity crystallized. That career arc is the product thesis in biographical form: he spent twenty years watching enterprises pay enormous sums for legacy MDM platforms that required extracting data into a separate system, hiring specialists to run them, and waiting months for deployment, then watched Databricks eliminate the architectural justification for all of that. He completed a program at Harvard Business School, is an Advisor and Investor at Knowi (a BI platform integrating analytics across data types), and founded Frisco Analytics alongside LakeFusion as a Databricks professional services entity that generated early customer relationships and product feedback before the software company stood on its own. He also launched Mio Home Services in July 2023, a home maintenance venture, which is either a genuine entrepreneurial detour or an experiment in marketplace operations that informed how he thinks about service delivery, which is the operational heart of an MDM deployment company. His LinkedIn posts are operational rather than promotional: he celebrates team deployments by name, calls out specific engineers who executed, and writes about Databricks architecture tradeoffs for data leaders. He is clearly not building LakeFusion as a vehicle for personal brand. He is building it because he spent two decades inside the problem and finally has the platform architecture to solve it properly.
What to show them
The Full Stack roles build the LakeFusion UI and platform surface: the interfaces through which data stewards configure entity resolution rules, review golden records, manage survivorship logic, and trigger syncs. This is not a consumer product. The users are data engineers and MDM administrators. The UI needs to be functional, fast, and deeply integrated with the platform's API surface. The AI/ML Engineer role builds and improves the entity resolution and deduplication models that sit at the heart of the product: LLM-based matching, vector embeddings for record similarity, and the classical ML approaches that handle high-volume deduplication cost-effectively.
A cold email that works at LakeFusion
What LakeFusion screens for
Silverton Partners leads this round and is the most important signal. They are an Austin-based venture firm with a concentrated portfolio of enterprise and B2B software companies. They back companies with genuine technical differentiation and push hard on enterprise GTM. Their portfolio includes companies across data infrastructure, SaaS, and developer tools. When Silverton leads an enterprise data infrastructure seed, they are expecting aggressive customer expansion in healthcare, financial services, and manufacturing, the three sectors LakeFusion has named explicitly. That is a commercial hiring mandate alongside the engineering one. Carbide Ventures, the existing investor from the November 2025 round, re-upped. That is the clearest possible internal signal: the investors closest to the company's day-to-day progress chose to put in more money. Carbide focuses on AI, data, and enterprise infrastructure. Their GP Pankaj Tibrewal noted that AI is not just driving demand for MDM, it is transforming how MDM itself gets done. That framing shapes the hiring bar: LakeFusion needs engineers who understand both the AI layer (entity resolution, LLM-based matching) and the data infrastructure layer (Databricks, Delta Lake, lakehouse architecture). The operational signal is equally important. Vikas posted publicly about completing five LakeFusion deployments in four days. That is not a press release claim. That is a live team executing at speed with a real customer queue. A team of 25 completing five enterprise MDM deployments in four days is running at a pace that requires more people immediately.
Tailor your CV to the specific LakeFusion role rather than sending a general one. Applications that mirror the language of the job description clear automated filters at a materially higher rate.
Don't make these mistakes
Don't pitch generic engineering experience without anchoring it to enterprise data, Databricks, or MDM specifically. Vikas came up through Informatica and two decades of data management consulting, so he will filter out anyone who treats LakeFusion as a standard SaaS engineering role. For the senior US-remote roles (Principal Backend, PIM Engineering Lead, Senior MDM Architect), don't lead with cloud experience in the abstract without naming the specific data platform context. For data and integration roles, don't confuse analytical data engineering (dbt models, dashboards) with operational integration engineering (bidirectional CRM/ERP sync, CDC, schema drift handling): these are different problems and the team will know immediately. For the GCP and Platform Security role, don't present compliance framework knowledge (HIPAA, SOC 2) as a substitute for Databricks-specific security implementation experience. For Full Stack roles, don't submit a consumer product portfolio: the users here are data stewards and MDM administrators, not end consumers. For the AI/ML role, don't lead with general machine learning credentials without referencing entity resolution, record linkage, or deduplication specifically. For support roles, don't position yourself as someone looking to break into engineering: Level 2 support here means debugging live enterprise Databricks deployments with real production stakes, and the team will expect you to have done something close to that already. Across all roles, the application goes to careers@lakefusion.ai, not a form, not LinkedIn, not a recruiter. Send one tight email with a specific proof point in the first sentence.
Mistakes that kill LakeFusion applications
Don't send the same CV you sent everywhere else. At <50 people it's obvious, and it's the fastest rejection there is.
Lead with their problem, not your ambition. LakeFusion is focused on Enterprise AI is stalling not because models are bad but because the data underneath them is broken — show you understand that.
Most AI applications get ghosted. A day-five follow-up can double your response rate.
Applying to LakeFusion? Get the contact, not the form.
The LakeFusion interview process
3 stages · 7 days typical · take-home: yes · modelled from similar companies
We don't yet have verified candidate reports for LakeFusion. What follows is the typical process for a <50-person AI company — treat it as a model, not confirmed detail.
Interview stages
Intro Call
Video call · 30 min
Culture fit and role expectations
Founder or hiring manager
Technical Deep Dive
Video call or in-person · 60 min
Past projects and problem-solving approach
Technical founder or lead
Final Round
In-person or video · 45 min
Team fit and offer discussion
Founding team
LakeFusion take-home assignment
LakeFusion includes a take-home exercise in their interview process. For AI roles, this typically involves a practical problem that takes 2-4 hours. Focus on clean, working code over premature optimization. They're evaluating how you think and communicate, not just the solution.
LakeFusion interview timeline
LakeFusion runs about days from first contact to offer. The median for AI companies at <50 people is 10 days, so LakeFusion is faster than most.
Interviewed at LakeFusion?
Tell us how it went — stages, questions, timeline. Takes 90 seconds and it's how this page stays accurate for the next person.
Submit your LakeFusion interview experience →LakeFusion jobs, frequently asked questions
How many jobs does LakeFusion have open?
We're tracking 11 active openings at LakeFusion (verified May 2026).
Does LakeFusion hire remotely?
Currently, LakeFusion only has in-office roles in Austin.
What roles is LakeFusion hiring for?
LakeFusion is hiring across Engineering, Other. The most recent opening is Principal Backend Engineer.
How do I apply for a job at LakeFusion?
Click through to apply, or see our detailed guide on landing a job at LakeFusion.
Does LakeFusion respond to cold emails?
We haven't verified response rates at LakeFusion yet.
Who is the hiring manager at LakeFusion?
At this size, hiring is usually run by a founder or department head.
How competitive is it to get hired at LakeFusion?
Roles at <50-person AI companies typically draw 50-100 applicants in the first two weeks. Applying inside 72 hours of a posting going live is the single biggest lever you control.
How many rounds is the LakeFusion interview?
3 stages: Intro Call, Technical Deep Dive, Final Round.
Is the LakeFusion interview hard?
The interview emphasizes technical depth and system design over abstract problems. Hardest stage: Technical Interview.
Does LakeFusion give a take-home task?
Yes, LakeFusion includes a take-home assignment.
How long does LakeFusion take to get back to you?
Around 7 days across the full process.
What should I prepare for the LakeFusion interview?
Prepare for technical depth and system design. A <50-person startup wants proof you can ship, not that you can whiteboard.
Where is LakeFusion based?
LakeFusion is headquartered in Austin, US.
Get LakeFusion roles before they're posted
A role stays uncontested for about four days. Here's the window — and where we put you in it.
From $9/month, cancel any time.
Watching LakeFusion
0 applicantsRole spotted & verified
1You get the alert
1You've applied
~8Hits the job boards
250+