Databricks Technical Delivery Lead

Databricks Technical Delivery Lead

Technical Delivery Manager, Customer Success | US-Based

ROLE SUMMARY

Our client is a fast-growing, AI-native data platform company built natively on the Databricks Lakehouse, on a mission to turn messy, disconnected enterprise data into a trusted asset that drives better decisions. We are seeking a hands-on technical delivery leader who pairs deep Databricks/Spark engineering depth with delivery ownership and a product mindset. This is not an MDM-tools or pure-consulting role, we need someone who can get into the platform, spot Spark anti-patterns, and coach engineering teams through live production issues at existing customers, not just manage a project plan.

WHY THIS ROLE

• Join at an early, high-growth stage with direct visibility to the Chief Architect and founding leadership, your fingerprints will be on how the delivery function is built, not just how it runs

• Work hands-on with real Spark/Databricks engineering challenges at enterprise scale, not slide decks or status trackers

• Shape how the company scales technical delivery from single accounts to a full portfolio of enterprise engagements

WHAT YOU'LL DO

• Manage delivery of platform implementations for enterprise customers

• Own the customer relationship on technical outcomes and timelines

• Translate customer needs into engineering work streams and prioritize across competing demands

• Solve complex customer problems hands-on while delegating execution to engineers

• Coach and enable existing solutions engineers to triage and resolve production issues at live customers

• Communicate status, risks, and blockers to customers and internal stakeholders

• Scale from owning single customer accounts to managing multiple concurrent engagements

WHAT YOU NEED

• Strong hands-on expertise with Spark and Databricks, including PySpark, performance tuning, and the ability to spot anti-patterns in existing implementations

• Track record solving hard customer problems spanning implementation, data quality, architecture, and integration

• Experience working at scale in fast-moving tech environments

• MDM, enterprise data platforms, or data management exposure is a plus, but not a substitute for direct Databricks/Spark fluency

• Comfort with ambiguity and ability to prioritize in complex, multi-stream environments

WHO THRIVES HERE

• You'd rather diagnose a slow Spark job yourself than wait on a ticket queue

• You've led delivery in fast-moving, high-caliber environments and want more ownership, not less

• You see data platforms as a product to be shaped, not just a project to be shipped