Engineering Manager - Query Optimization

    • Databricks Inc
  • Mountain View, CA
  • Posted 50 days ago | Updated 3 hours ago

Overview

On Site
USD 192,000.00 - 260,000.00 per year
Full Time

Skills

Query optimization
Data warehouse
Organizational structure
IT architecture
Data storage
Team leadership
Product management
Computer science
Databricks
Data
Transportation
Artificial intelligence
Python
SQL
Scala
R
Cloud computing
Leadership
Innovation
Extract
transform
load
Analytical skill
Management
Recruiting
Organized
Strategy
Roadmaps
IMPACT
Database
Design
Testing
Personas
Training

Job Details

P-931

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 Query Optimization team, a core part of the Databricks Data Intelligence Platform, that is responsible for transforming customer workloads, whether they are specified with Python, SQL, Scala or R to efficiently run on a scalable and distributed environment that is available on all three of the top cloud platforms. We innovate and leverage techniques that range from traditional approaches to making advanced, AI-based, data-driven decisions in order to run workloads efficiently and lead the industry when it comes to scale, performance, and cost. We're seeking a dedicated Engineering Leader to drive innovation and deliver robust solutions through query optimization across an incredibly diverse and growing set of customer workloads that range from ETL to data warehousing analytic queries and AI.

The key responsibilities include:
  • Leading a talented engineering team in Query Optimization
  • Overseeing sustained recruitment of top-tier talent, fostering a well-organized and synergistic team structure, and collaborating effectively with internal and external stakeholders
  • Implementing robust processes to efficiently execute product vision, strategy, and roadmap in alignment with organizational goals and priorities

The impact you will have:
  • Lead development for the query optimizer, a core part of Databricks Data Intelligence Platform
  • Define, shape, and drive the future of Databricks Data Intelligence Platform
  • Grow a world-class team of software engineers working query optimization; hire top-notch staff+ level talent
  • 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

What we look for:
  • 5+ years experience working in a related system with an emphasis on query optimization and database internals
  • A passion for database systems, storage systems, distributed systems, language design, query optimization and performance
  • Can ensure the team builds high quality and reliable infrastructure services; experience being responsible for testing, quality, and SLAs of a product; previous experience building and leading teams in a complex technical domain, such as on distributed data systems or database internals
  • Ability to attract, hire, and coach engineers who meet the Databricks hiring standards; can up level existing team via hiring top-notch senior talent, growing leaders and helping struggling members; can gain trust of team and guide their careers; experience managing distributed teams preferred
  • Comfort working cross functionality with product management and directly with customers; ability to deeply understand product and customer personas
  • BS in Computer Science (Masters or PhD Preferred)

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents base 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 utilizes 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 .

Local Pay Range
$192,000-$260,000 USD

About Databricks

Databricks is the data and AI company. More than 10,000 organizations worldwide - including Comcast, Cond 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 , and .

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.