---
title: 'Lakebase Sales Specialist at Databricks'
canonical: 'https://feeny.ai/job/lakebase-sales-specialist-databricks-amsterdam-6pz119f96nvx'
type: 'job'
last_seen: '2026-09-05'
---

# Lakebase Sales Specialist at Databricks

- **Company:** Databricks
- **Location:** Amsterdam, Netherlands
- **Posted:** 2026-06-23
- **Last confirmed live:** 2026-09-05
- **Apply:** https://databricks.com/company/careers/open-positions/job?gh_jid=8569524002

## Job description

SLSQ327R348

Databricks is seeking a Lakebase Sales Specialist to help customers modernise their operational data foundation with Databricks Lakebase, our fully-managed Postgres offering for intelligent applications. This high-impact role sits within the Lakebase Go-To-Market team and partners closely with regional Account Executives to drive adoption of Lakebase with platform, application, and data teams.

Lakebase gives customers a unified, governed foundation for operational workloads and AI-native applications, helping them move away from a fragmented estate of point databases toward a modern, scalable, serverless Postgres service. If you want to be at the forefront of operational databases for AI and intelligent applications at one of the fastest-growing data and AI companies in the world, this is your opportunity.

The impact you will have:

- Drive new Lakebase revenue by identifying, qualifying, and driving Lakebase activations and consumption within a defined territory, in partnership with regional Account Executives and the broader account team
- Lead with outcomes for key Lakebase personas, including platform teams and developers, data teams, and central IT, articulating how Lakebase helps them ship features faster, simplify operational data architectures, and improve governance and cost efficiency
- Sell the value of fully-managed Postgres for intelligent applications, positioning Lakebase as the optimal choice for operational workloads that power real-time, AI-driven experiences
- Run complex sales cycles from discovery and value hypothesis through commercial negotiation and close, navigating executive, technical, and line-of-business stakeholders
- Orchestrate proof-of-value and POCs that validate Lakebase’s benefits for OLTP-style workloads, reverse ETL, and AI/ML-driven applications, in partnership with solution architects and specialists
- Compete and win against legacy and cloud-native operational databases by leveraging our compete assets, benchmarks, and customer references
- Align to measurable business outcomes such as performance, developer productivity, time-to-market for new features, cost reduction, and simplification of the operational data landscape
- Partner cross-functionally with Product Management, Marketing, Customer Success, and Partner teams to shape territory plans, launch plays, and co-selling motions with key ISVs and GSIs
- Enable the field by sharing Lakebase best practices, success stories, and sales motions with broader sales teams, helping scale Lakebase proficiency across the organisation

What success looks like in this role:

This role requires the ability to operate across two key motions simultaneously:

- Establish top strategic focus accounts by engaging application development teams to create net-new intelligent applications leveraging Lakebase
- Drive longer-term Postgres standardisation and migration within Databricks' most strategic accounts

Success in this role requires strength in four areas:

- Business ownership: Operate at a business-unit level by tracking revenue, pipeline, and key observations, and by identifying areas needing additional focus or support.
- Strategic account engagement: Partner with account teams to engage priority accounts, driving strategic opportunities from initial engagement through successful outcomes.
- Field, account, & customer enablement: Align customers and the field on the value of Lakebase by equipping AEs and SAs with the messaging and execution motions needed to confidently own accounts without specialist intervention.
- Market voice and thought leadership: Develop an internal and external presence, and by representing Databricks at key first- and third-party events.

The interview process is designed to evaluate candidates across all four of these dimensions.

What we look for:

- Relevant enterprise sales experience, consistently exceeding quota in complex, multi-stakeholder deals
- Proven success selling data platforms, operational databases (e.g., Postgres, MySQL, cloud-native DBaaS), or adjacent data/AI infrastructure to technical buyers and business leaders
- Strong understanding of modern data and application architectures, including cloud-native services, microservices, event-driven systems, and how operational data underpins AI and analytics strategies
- Ability to sell to both technical stakeholders (developers, architects, data engineers) and business stakeholders (product leaders, operations, line-of-business owners)
- Demonstrated experience leading specialist or overlay motions, working jointly with core Account Executives to create and progress opportunities
- Executive presence with the ability to whiteboard architectures, lead C-level conversations, and build trust with senior decision makers
- Strong value selling skills: adept at discovering pain, building a business case, and tying technical capabilities to clear, quantified outcomes
- Excellent communication, storytelling, and negotiation skills, with comfort presenting to both large and small audiences
- Bachelor’s degree

## Preferred qualifications

- Experience selling Postgres, operational databases, OLTP workloads, or transactional cloud database services, ideally within large or strategic accounts
- Familiarity with data platforms, lakehouse architectures, and cloud ecosystems (AWS, Azure, GCP), including how operational databases fit within broader data and AI strategies
- Understanding of reverse ETL, real-time decisioning, and operational analytics use cases, and how they drive value for customer-facing and internal applications
- Exposure to AI-native and agent-driven applications that depend on low-latency, highly scalable operational data services
- Prior experience in a high-growth, category-creating environment, helping shape new plays, messaging, and customer narratives
- Experience collaborating with partners and ISVs to drive joint pipeline and co-sell motions

This description is intended to outline the core responsibilities and qualifications for the Lakebase Sales Specialist role. Actual responsibilities may evolve as the Lakebase product and go-to-market motions continue to grow and mature.

## About Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on [LinkedIn](https://www.linkedin.com/company/databricks), [X](https://x.com/databricks), [YouTube](https://www.youtube.com/@Databricks), and [Instagram](https://www.instagram.com/databricksinc/?hl=en).

## Benefits

At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click [here](https://docs.google.com/document/d/154un3e8Xav4BceOSlcYFZRGEuQI54xMxVydRwQn54eQ/edit?usp=sharing).

Our Commitment to Diversity and Inclusion

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

## About Databricks

## Company Overview
- **One-liner**: Databricks provides a unified data and AI platform built on an open lakehouse architecture, enabling organizations to manage data, analytics, and AI at scale.
- **Entity Type**: Private (late-stage, last reported valuation ~$43B in 2021, but current valuation not publicly disclosed)
- **Headquarters**: San Francisco, California, USA
- **Founded**: 2013
- **Founders**: Original creators of Apache Spark™, Delta Lake, MLflow, and Unity Catalog (co-founders include Ali Ghodsi, Matei Zaharia, Ion Stoica, Patrick Wendell, Reynold Xin, among others)

## Core Business
- Primary industry: Data & AI Platform / Enterprise Software
- Target customers: B2B – Enterprise, SMB, and government organizations; over 20,000 customers worldwide, including 70% of the Fortune 500
- Mission: “Simplify and democratize data and AI, helping data and AI teams solve the world’s toughest problems.” [databricks.com](https://www.databricks.com/company/about-us)

## Products & Services
- **Databricks Data Intelligence Platform**: Unified platform for data engineering, data warehousing, data science, machine learning, and AI. It integrates open-source technologies like Apache Spark, Delta Lake, MLflow, and Unity Catalog.
- **Lakebase**: Serverless Postgres database integrated with the lakehouse, built for the AI era.
- **Genie**: AI-powered natural language assistant for data insights and querying.
- **Agent Bricks**: Tools for building AI agents that continuously improve quality and accuracy on an organization’s data.
- **Additional offerings**: Data warehousing, business intelligence, governance, data engineering, and AI/ML services.

## Market Standing
- **Valuation/Market Cap**: Not publicly available (private company; last reported valuation of $43B in 2021 from a Series I round, but no recent official disclosure)
- **Key Metric**: Over 10,000 employees; 20,000+ customers; 70% of Fortune 500; 1,200+ global partners [databricks.com](https://www.databricks.com/)
- **Notable Investors/Partners**: Not explicitly listed in search results, but known investors include Andreessen Horowitz, Tiger Global, Microsoft, and others. Partners include major cloud providers (AWS, Azure, GCP) and consulting firms.
- **Growth Signals**: Headcount of 10,000+ employees; offices in 30+ locations across 20+ countries; 5x Leader in Gartner® Magic Quadrant™ Reports; LinkedIn job postings growing 26.7% year-over-year (783 active positions) [linkedin.com](https://www.linkedin.com/company/databricks)

## Competitive Advantages
- **Open lakehouse architecture**: Combines data lake and data warehouse capabilities with open-source standards, avoiding vendor lock-in.
- **Founding team behind Apache Spark, Delta Lake, MLflow**: Deep technical credibility and active open-source community.
- **Unified platform**: Single solution for data engineering, analytics, and AI, reducing complexity for enterprises.
- **Strong data governance**: Unity Catalog provides centralized access control and lineage.
- **AI-native**: Built-in AI capabilities (Genie, Agent Bricks) that leverage an organization’s own data.

## Strategic Focus
- Expanding AI capabilities with natural language interfaces and autonomous agents.
- Deepening integrations with cloud providers and open-source ecosystems.
- Scaling enterprise sales and global footprint (30+ offices, focus on EMEA and APAC).
- Cultivating a developer and data science community through university programs and open-source contributions.

## Why Work Here
- **Culture**: Described as “innovators, builders and truthseekers” with a focus on solving hard technical problems. Emphasizes inclusion, diversity, and equity, including closing the pay gap and removing unconscious bias from recruitment. [databricks.com](https://www.databricks.com/company/careers)
- **Work Environment**: Hybrid/flexible work model; benefits and perks include health, well-being, and flexible ways of working. Offices in major cities globally.
- **Engineering Culture**: Strong emphasis on open-source, AI, and data infrastructure. Opportunities for interns and new grads to contribute to core platform. Hackathons, board game nights, and social events.
- **Growth**: Fast-growing company (10,000+ employees, 20,000+ customers) with ambitious scaling plans, offering career advancement in engineering, sales, product, and more.

## Sources
1. [Databricks About Us](https://www.databricks.com/company/about-us)
2. [Databricks Careers](https://www.databricks.com/company/careers)
3. [Databricks Homepage](https://www.databricks.com/)
4. [Databricks LinkedIn](https://www.linkedin.com/company/databricks)

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