Director of Engineering (Lakeflow)

(P-1384)

About The Team

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs.

Ingesting data into the Lakehouse is a strategic area of investment for Databricks and a key enabler for Data and AI workflows. Lakeflow Connect is looking to solve this problem by providing ready-to-use, point-and-click connectors for a wide variety of sources, including enterprise applications (like Salesforce, Workday, ServiceNow, SharePoint), databases (e.g., SQL Server), cloud storage, message queues, and local files.

In addition to being an important part of Lakeflow and Data Engineering, Connect is also a key platform capability. Every surface in Databricks (Dashboards, Notebooks, SQL, AI) requires ingestion capabilities and the lead for this role will need to work closely with other products to embed Connect into these surfaces.

We are looking for a senior leader to run our Connect organization in India. This is a great opportunity to lead a key strategic initiative for Databricks. The ideal candidate would have experience leading teams that build Data infrastructure as well as interest / experience in running product centric organizations. We would also look for the ability to collaborate effectively across time zones as well organizational boundaries.

The Impact You Will Have

• Solve real business needs at a large scale by applying your software engineering
• Ensure consistent delivery against milestones and strong alignment with the field working 'two-in-a-box' with product leadership
• Evolve organizational structure to align with long term initiatives, build strong '5 ingredient' teams with good comms architecture
• Manage technical debt, including long term technical architecture decisions and balance product roadmap
• Leading and participating in technical, product, and design discussions
• Building, managing, and operating a highly scalable services in the cloud
• Growing leaders on the team by providing coaching, mentorship, and growth opportunities
• Partnering with other engineering and product leaders on planning, prioritization and staffing
• Creating a culture of excellence on the team while leading with empathy

What We Look For

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, please visit https : / / www.mybenefitsnow.com / databricks.

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

Saas, Technical Architecture, Software Engineering, data infrastructure