SLSQ327R318
Databricks is seeking a Lakebase Sales Specialist to help customers modernize 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 within our Retail vertical 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, multi-threaded 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 organization.
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 standardization and migration within Databricks' most strategic accounts.
Candidates should demonstrate how they can act as a force multiplier across multiple dimensions of the business.
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 across the global DB700, 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 by contributing to global AMAs and internal forums, 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
- 7+ years of enterprise SaaS 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 or equivalent practical experience.
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.
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipated utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.
About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
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.
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.
Skills Required
- 7+ years of enterprise SaaS sales experience
- Proven success selling data platforms or operational databases to technical buyers
- Strong understanding of modern data architectures
- Ability to sell to technical and business stakeholders
- Exemplary communication and negotiation skills
- Bachelor's degree or equivalent practical experience
Databricks Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Databricks and has not been reviewed or approved by Databricks.
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Equity Value & Accessibility — Equity grants and RSUs are a major part of total compensation and are highlighted for meaningful upside potential. Stock-based awards and refreshers contribute to strong overall pay positioning across senior technical and go-to-market roles.
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Healthcare Strength — Medical, dental, and vision coverage are complemented by mental-health resources, an EAP, and wellness reimbursements. Health benefits are consistently framed as comprehensive and competitive.
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Parental & Family Support — Paid parental leave for all parents, fertility support, and backup care options provide tangible assistance for family needs. Hybrid work norms and team-day structure further ease coordination for caregivers.
Databricks Insights
What We Do
As the leader in Unified Data Analytics, Databricks helps organizations make all their data ready for analytics, empower data science and data-driven decisions across the organization, and rapidly adopt machine learning to outpace the competition. By providing data teams with the ability to process massive amounts of data in the Cloud and power AI with that data, Databricks helps organizations innovate faster and tackle challenges like treating chronic disease through faster drug discovery, improving energy efficiency, and protecting financial markets.
