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How to Actually Get Hired
Who reads applications, which channel gets a reply, and what they screen for.
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.
What gets their attention
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.
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
Their focus: 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.
Mistakes that kill 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.
Frequently asked questions
How do I apply to LakeFusion?
Through the roles on our LakeFusion jobs page, or directly to a founder or department head if you can reach them. At <50 people, direct outreach outperforms the form.
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.
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