Updated Jan 21, 2026 using last 90 days postings.

Databricks Hiring Trends – January 2026

Databricks is rapidly scaling its Data Engineering and Infrastructure capabilities, focusing heavily on expanding enterprise sales teams across key international markets such as France, Germany, and the US, with a strong emphasis on driving new business and deepening strategic customer relationships in sectors like media, financial services, and energy. The company is also investing in advanced AI and machine learning operations, particularly around GenAI and large language model infrastructure, to support their Lakehouse platform's growth and performance at scale. Cross-functional roles in sales enablement, technical program management, and solutions architecture indicate a comprehensive effort to support complex, large-scale deployments of their unified data analytics and AI platform.

Note: These dashboards are not the source of truth. Job posting data can include duplicates and may double count roles. Treat the results as a sample that helps explain what the postings suggest about hiring focus. Summaries are generated with an LLM and may contain errors or omissions. For the most accurate and complete information, research the company directly.

Tracked openings

658

Remote share

9%

Top location

CA, US

Top category

Data Engineering And Infrastructure

Inside The Product

Summary

Databricks builds a unified data analytics and AI (Lakehouse) platform used by over 10,000 organizations, including major media and enterprise customers. Current hiring emphasizes scaling enterprise GTM, verticalized product marketing and enablement, and operationalizing large-scale GenAI/LLM infrastructure and cloud integrations.

What They Build

  • Unified Data Analytics & AI (Databricks Lakehouse) for big data, analytics and ML/AI
  • Large-scale GenAI / LLM platform and GPU-backed infrastructure with capacity planning
  • Cloud-native integrations across AWS, Azure and GCP and Apache Spark-based engineering
  • Verticalized solutions and go-to-market tooling (industry positioning, sales plays, enablement)

Customers & Users

  • Large enterprises and Fortune 500 customers across industries
  • Industry verticals: Media, Financial Services (FSI), Energy, Manufacturing
  • Digital-native and emerging commercial customers
  • Sales and partner technical champions involved in platform adoption

Workflows & Systems

  • Enterprise sales motions: new-logo hunting, account planning, MEDDPICC, value selling and consumption-based land-and-expand
  • Technical evaluation: hands-on POCs, Apache Spark programming, reference architectures and integration with third-party cloud services
  • Cross-functional collaboration between Sales, Field Engineering, Professional Services, Product, Marketing and Customer Success
  • Operational programs for GenAI: LLM/GPU capacity planning, production ops, risk/analytics-driven decisioning and agile program management (Jira)
  • Regional GTM scale: building regional sales capacity, enablement teams and industry marketing to drive pipeline

Role Insights

Enterprise Sales & Account Management

Hiring hunters and expansion reps to grow regional footprints (France, EMEA), focus on new-logo acquisition, quota over-achievement and consumption-based land-and-expand motions using MEDDPICC and value selling.

Data Engineering & Infrastructure

Scaling teams that architect and deliver Lakehouse deployments and cloud integrations for big data analytics and AI across customer accounts.

Machine Learning & AI Engineering / GenAI Ops

Recruiting TPMs and ops leads to run LLM/GPU-backed platforms in production, own capacity planning, cross-functional launches and steady-state GenAI operations.

Solution Architecture

Hiring hands-on architects to lead technical evaluations, author reference architectures, run Spark demos and integrate Databricks with customers' cloud ecosystems.

Sales Enablement & Learning

Building regional enablement teams to up-skill sellers, pre-sales and services so they can drive adoption and democratization of data and AI.

Industry Marketing & Product Marketing

Growing vertical marketing to translate technical capabilities into industry-specific positioning, sales tools, and demand-generation programs (e.g., Energy, Media, FSI).

Software Engineering Leadership & Backend Engineering

Seeking leaders and backend engineers with distributed systems, Scala/Python/Java and cloud experience to scale core platform performance and reliability.

Digital Transformation & GTM Leadership

Hiring senior revenue leaders to design data-driven sales operations, expand SaaS revenue motions, and create scalable go-to-market structures across regions.

Team Focus

  • Data Engineering And Infrastructure: 119 roles (18.1%)
  • Enterprise Sales And Account Management: 61 roles (9.3%)
  • Backend Engineer: 45 roles (6.8%)
  • Software Engineering Leadership: 43 roles (6.5%)
  • Engineering Management: 30 roles (4.6%)
  • Solution Architecture: 30 roles (4.6%)
  • Sales: 26 roles (4.0%)
  • Technical Support And Engineering: 23 roles (3.5%)

Skill Stack

Data Engineering And Infrastructure

Apache Spark Delta Lake MLflow Cloud Platforms Big Data Analytics Data Engineering Data Science Distributed Systems

Enterprise Sales And Account Management

SaaS Sales Enterprise Account Management Big Data and AI Solutions Cloud Vendor Collaboration Sales Methodologies Customer Relationship Management Quota Achievement Solution Selling

Backend Engineer

Scala Python Java Distributed Systems Cloud Infrastructure Microservices Containerization Databases

Software Engineering Leadership

Technical Team Leadership Cloud-Native Architectures Data Governance Secure ML Operations Distributed Systems Observability Platforms Customer-Facing Technical Roles Cross-Functional Collaboration

Engineering Management

Technical Team Management Pre-Sales Leadership Cross-Functional Collaboration Security Engineering Hiring and Mentorship Consumption-Driven Business Models Technical Qualification Architecture Review

Solution Architecture

Solution Architecture Design Big Data Analytics Public Cloud Platforms Use Case Discovery Customer Engagement Technical Pre-Sales Reference Architectures Technical Leadership

Location Footprint

  • CA, US: 141 roles (21.4%)
  • India: 75 roles (11.4%)
  • WA, US: 53 roles (8.1%)
  • Remote (US): 39 roles (5.9%)
  • Netherlands: 38 roles (5.8%)
  • United Kingdom: 35 roles (5.3%)
  • Singapore: 32 roles (4.9%)
  • Germany: 31 roles (4.7%)

Seniority Mix

  • Mid: 412 roles (62.6%)
  • Senior: 217 roles (33.0%)
  • Entry: 24 roles (3.6%)
  • Intern: 5 roles (0.8%)

Role Types

  • full_time: 654 roles (99.4%)
  • internship: 4 roles (0.6%)

Hiring Cadence