Engineering Manager - Money

Reposted 23 Days Ago
Be an Early Applicant
2 Locations
In-Office
181K-241K Annually
Senior level
Big Data • Machine Learning • Software • Analytics • Big Data Analytics
The Role
As the Engineering Manager for the Money team, you will oversee engineering processes, hire and develop talent, enforce technical standards, and coordinate project execution across teams to enhance monetization functionalities.
Summary Generated by Built In

P-1334

At Databricks, we are obsessed with Data + AI to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high-value challenges that are central to their missions.

Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, CA to a global organization with over 6500 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest-growing SaaS companies in the world.

The Money team's mission at Databricks is to maximize the value that our customers derive from their investments in data projects. We accomplish this through innovative commercialization strategies, timely & accurate metering & billing, cost optimization tools, intelligent resource usage controls, and cutting-edge engineering. We provide a seamless and consistent set of platforms to enable all Databricks products to reach customers quickly, and sustainably. As an Engineering Manager in Money, you will be key to one of Databricks’ most central engineering orgs. You will own critical components that form the backbone of our business, working closely with infrastructure as well as product teams in bringing critical monetization functionality to Databricks customers.

The impact you will have:
  • Hire great engineers to build an outstanding team and support their career development by providing clear and timely feedback.
  • Ensure high technical standards by instituting processes (architecture reviews, testing) and culture (engineering excellence).
  • Work with engineering and product leadership to build a long-term roadmap.
  • Coordinate execution and collaborate across teams to successfully deliver cross-cutting strategic projects.
What we look for:
  • 10+ years of extensive experience with large-scale distributed systems alongside processes around testing, monitoring, SLAs etc
  • 5+ years of engineering management experience, building, managing and mentoring high-performing software engineering teams
  • Demonstrated success in collaborating with multiple cross-functional stakeholders to align system features and architecture, to deliver impactful platform projects.
  • Experience in developing and implementing proactive mechanisms for failure detection and incident prevention.
  • Excellent leadership, communication, and project management skills.
  • BS (or higher) in Computer Science, or a related field.

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
$181,300$241,075 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.

Top Skills

Spark
Computer Science
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The Company
New York, NY
2,200 Employees
Year Founded: 2013

What We Do

As the leader in Unified Data Analytics, Databricks helps organizations make all their data ready for analytics, empower data science and data-driven decisions across the organization, and rapidly adopt machine learning to outpace the competition. By providing data teams with the ability to process massive amounts of data in the Cloud and power AI with that data, Databricks helps organizations innovate faster and tackle challenges like treating chronic disease through faster drug discovery, improving energy efficiency, and protecting financial markets.

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