Role Description & Responsibilities
Data Analytics
About Databricks
Databricks is a high-growth technology leader building scalable solutions for global users. Millions of companies and teams rely on their infrastructure and services to execute high-value workflows, analyze massive datasets, and scale modern operations.
CadetX Candidate Advantage: As an applicant for this Data Analytics role, you are evaluated on practical proficiency with real-world query execution, data pipelines, and clear stakeholder communication.
CadetX Role Brief & Company Specifications
Role Mission & Impact
Enterprise customers are investing in AI, but most are stuck between a successful pilot and real organizational adoption. The gap is not technology. It is whether the workforce can change how it works.
You will own end-to-end workforce transformation engagements with Databricks' largest customers. You will diagnose where a customer's workforce is today, define what needs to change, build the transformation plan, and drive execution until adoption sticks. You are the directly responsible individual for each engagement, not a contributor to someone else's project.
Key Responsibilities & Day-to-Day Scope
- ✓ Own the full transformation lifecycle for each customer, from workforce assessment through capability pathways, operating rhythm, and measurement. You build the plan and you execute it.
- ✓ Run 2 to 3 concurrent engagements across different formats. These range from short-cycle assessments (2 to 4 weeks) to coached transformations (8 to 12 weeks) to deep embedded engagements (12 to 16 weeks). You will manage a mixed portfolio simultaneously.
- ✓ Design for multiple organizational layers within a single engagement. That means building executive sponsorship with CDOs, CIOs, and CHROs while also architecting the manager enablement and individual contributor adoption layers underneath.
- ✓ Drive execution, not just planning. You will stand up the operating rhythm, coach internal champions, unblock adoption barriers, and adjust the plan when reality diverges from the model.
- ✓ Design the human-agent collaboration model for each customer's workforce. Assess workflows and distinguish what should stay human from what should be automated, agent-assisted, or fully agent-led. Design differentiated pathways for builders in technical roles and users in workflow roles.
- ✓ Shape how engagements are scoped and priced. You are closest to the work and will ensure that commercial commitments are deliverable.
- ✓ Turn what you learn into repeatable tools and playbooks that can scale beyond practitioner-led delivery.
- ✓ Partner with technical deployment, AI transformation, and account teams. Other teams build and land the solution. You own what happens after.
- ✓ 8 or more years leading workforce or organizational transformation in a technology adoption context. You have executed transformations and owned outcomes, not just designed programs.
Official Qualifications & Technical Requirements
- • You have led conversations with C-suite or VP-level sponsors and influenced how organizations adopt technology at scale.
- • You have done the work, not just designed a curriculum about it. The strongest backgrounds include customer-side data or engineering leaders who drove transformation, former solutions architects or engineers who moved into transformation roles, and consultants with hands-on delivery experience.
- • You can assess a workflow, identify what needs to change, and design the capability pathway to get there.
- • You understand change management, including sponsorship models, adoption curves, resistance patterns, and how to build internal champions.
- • You are comfortable with ambiguity. You will be building the playbook as you go, not executing a mature one.
- • You are comfortable with commercial conversations, including engagement scoping, pricing input, and ensuring delivery commitments are realistic.
- • Familiarity with data and AI platforms and the enterprise adoption challenges they create.
- • A background in professional services, management consulting, or customer success is a plus.
- • Experience measuring behavior change tied to business value, not just completions or satisfaction scores, is a plus.
Preferred Skills & Technology Stack
- + Experience working with cloud data warehouses (Snowflake, BigQuery, or Amazon Redshift).
- + Familiarity with Git version control and collaborative code review workflows.
- + Demonstrated portfolio or capstone projects exhibiting practical end-to-end analytics problem solving.
Tech Stack & Tools in this role
Expected technical competencies for Day 1 productivity:
★ Life & Culture at Databricks
Verified EmployerDatabricks champions rigorous analytical discipline, continuous learning, and low-ego teamwork. Team members enjoy flexible hybrid allowances, learning stipends, and structured mentorship to fast-track career mobility.