Synced from Greenhouse · Aug 3

GTM Analytics Engineer

DatabricksBelgrade, SerbiaPosted Aug 3, 2026
Analytics EngineerSenior
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Aug 3
Posted
Greenhouse
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Job descriptionReq 8638849002

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 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, X, YouTube, and Instagram.

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.

View original posting on Greenhouse

What applying to Databricks usually looks like

Based on publicly available information, candidates applying through greenhouse for roles at Databricks can generally expect a structured process typical of this ATS. This commonly begins with an online application and resume screen, followed by a recruiter conversation to discuss background and role fit. Depending on the position, candidates may encounter technical assessments, take-home exercises, or case studies, particularly for engineering, data, and analytical roles. The process may include multiple stages such as hiring manager conversations, panel discussions, and team or cross-functional interviews. Response times vary and communication is typically managed through the greenhouse platform, including scheduling and status updates. Candidates should prepare to discuss relevant experience, technical skills, and role-specific scenarios, as greenhouse-based processes commonly emphasize structured evaluation criteria across candidates to support consistent, comparative hiring decisions throughout the pipeline.

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GTM Analytics Engineer
Databricks · Belgrade, Serbia
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