SLSQ327R638
The GTM Solutions & Governance team sits within GTM StratOps/Analytics (SGO) and is tasked with making our GTM data estate trustworthy, enriched, and self-serviceable. As a distinct function from traditional analytics, we own the advanced AI/agent solutions and complex automation built on top of our data. You will work alongside experts in GTM Automation, GTM Alerting, Peer Similarity, and Data Governance to elevate how our GTM organization operates.
The Role
We are looking for a Senior GTM Analytics Engineer to build advanced generative AI applications, automated pipelines, and agentic solutions to optimize our revenue operations. You will own the development of data pipelines handling both structured and unstructured data, architect high-level AI implementations like Agentic CDPs, and drive our internal Databricks on Databricks (DBX@DBX) initiatives.
Core Responsibilities
- Agentic CDP & Identity Resolution: Architect and deploy Agentic Customer Data Platform (CDP) capabilities to perform intelligent identity resolution, driving automated and highly accurate data enrichment for accounts and contacts.
- GenAI & Agent Architecture: Design LLM-powered systems and internal agents to automate KPI root-cause analysis, generate business insights, and streamline GTM communication.
- Advanced Data Pipelines: Build and manage complex data pipelines to process structured and unstructured data, ensuring high-fidelity inputs for the GTM data estate while seamlessly integrating with our existing governance frameworks.
- GTM Systems Integration: Understand the technology stack and how data flows between critical systems like Salesforce, Xactly, and 6sense to ensure unified data architecture.
- Cross-Functional Partnership: Partner directly with Sales, Marketing, and RevOps leaders to turn strategic business problems into scalable, data-driven AI solutions.
What We Look For
- Technical Stack: You have expert proficiency in Python, SQL, and modern data pipelines. You also have experience with Salesforce or equivalent CRM systems.
- Platform Expertise: You will work every day with a variety of data using Databricks’ lakehouse platform. You will become an expert in using Databricks and complementary AI technologies to build production-grade solutions.
- Domain Experience: You typically have strong experience in data engineering, data science, or advanced analytics, with a background working closely with B2B sales, marketing, or finance data.
- Advanced Analytics Background: You have a strong track record in B2B SaaS, machine learning, and generative AI deployment.
- Execution Mindset: You excel in a collaborative environment and translate team member needs into clear deliverables. You work through dependencies, bottlenecks, and tradeoffs with ease.
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
- Expert proficiency in Python
- Expert proficiency in SQL
- Experience building and managing modern data pipelines for structured and unstructured data
- Production experience with Databricks and the lakehouse platform (DBX@DBX)
- Experience with Salesforce or equivalent CRM systems
- Experience integrating GTM systems such as Xactly and 6sense
- Background in data engineering, data science, or advanced analytics with B2B sales/marketing/finance data
- Proven track record deploying machine learning and generative AI / LLM solutions in production
- Experience architecting agentic solutions and identity resolution / CDP capabilities
- Strong collaboration, execution mindset, and ability to partner with Sales, Marketing, and RevOps
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 are a meaningful part of offers, and periodic tender opportunities and secondary options have made private equity more tangible for many employees. This perceived upside contributes to strong total-compensation sentiment in key roles.
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Healthcare Strength — Comprehensive medical, dental, and vision coverage is paired with mental‑health resources and wellness reimbursements, indicating a robust health package. Multiple summaries highlight broad coverage that employees can practically use.
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Leave & Time Off Breadth — Generous PTO, paid holidays/sick time, and fully paid parental leave are frequently described, with hybrid/remote flexibility common in the U.S. These policies expand time‑off accessibility across different life stages.
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.
