Senior Engineering Manager - Enzyme

Cacheflow; Mountain View (CA); On-site; USD 217,000 - 288,000; Full time

Job summary

Databricks is seeking an Engineering Leader to spearhead the Materialized Views team within the Lakeflow Engineering group. You will drive delivery of next-generation MV features for ETL workloads and query acceleration, and partner with product management and customers to define roadmaps.

You will recruit, coach and grow engineers, implement scalable processes, and ensure the delivery of high-quality, reliable infrastructure services across the platform.

Qualifications

• Leadership of engineering teams
• Experience building data infrastructure systems such as Spark or similar
• Ability to work with product management and customers

Responsibilities

• Lead an engineering team building the next-generation Materialized View features for the Lakeflow platform.
• Oversee recruitment and upskilling of team members.
• Build processes to implement product vision and strategy for the platform.
• Deliver high-quality, reliable infrastructure software.

Skills

Team leadership

Data infrastructure

Apache Spark

Database internals

Product collaboration

Customer interaction

Hiring & coaching

Testing & SLA

Job description

P-1110

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. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business.

We are the Lakeflow Engineering team, responsible for Databricks ETL product line such as Materialized Views, Structured Streaming, and Delta Live Tables. We run one of the world's biggest (if not the biggest) data engineering platforms - responsible for processing exabytes of data daily for tens of thousands of customers.

We're seeking a dedicated Engineering Leader to spearhead the Materialized Views engineering team. The team is responsible for building next generation Materialized View features for both ETL workloads and for query acceleration.

The main responsibilities include:

• You will lead an engineering team building the next-generation Materialized View features for the Databricks Lakeflow platform.
• You will oversee sustained recruitment of top-tier talent, and upskilling talent on the team.
• You will build processes to implement product vision and strategy, according to organizational goals and priorities.
• You will build software that is not just high quality but easy to operate.

What we look for:

• Minimum 3 years of experience in managing top-tier engineering teams
• 5+ years experience building data infrastructure systems such as Apache Spark™ or database internals.
• A passion for database systems, storage systems, distributed systems, or performance optimization
• Experience working with product management, and directly with customers; ability to understand customer needs.
• Can ensure the team builds high quality and reliable infrastructure services. Experience being responsible for testing, quality, and Service Level Agreements of a product. Experience building and managing teams in a complex technical domain, such as on distributed data systems or database internals.
• Expertise in attracting, hiring and coaching engineers, who will meet the Databricks hiring standards. Experience up-leveling teams via hiring top-notch talent and growing existing team members.

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.

Local Pay Range

$217,000 — $288,400 USD

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.