Sobre esta vaga de Senior Manager, Infrastructure Data Science na Databricks
RDQ225R487
Job Description
Databricks is looking for a Senior Manager, Infrastructure Data Science to shape the future of Databricks infrastructure through data science. You will tackle some of the most complex challenges related to capacity planning, performance optimization, reliability engineering, infrastructure efficiency, and customer experience. You will lead a team of data scientists and work directly in partnership with engineering leaders to empower them with data-driven insights and solutions.
At Databricks, we are obsessed with enabling data teams 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 7000 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.
Our engineering teams build highly technical products that fulfill real, important needs in the world. We constantly push the boundaries of data and AI technology, while simultaneously operating with the resilience, security, and scale that is critical to making customers successful on our platform.
The impact you will have:
- Thought leadership and strategic guidance on infrastructure planning, balancing current needs with future growth projections to ensure scalability and cost-effectiveness.
- Promote a data-driven approach to infrastructure decisions, influencing stakeholders across engineering, and support to leverage data science insights for high-impact, aligned strategies.
- Implement data-driven solutions to identify, predict, and mitigate infrastructure risks and failures, reducing downtime and improving system reliability and performance, directly impacting end-user satisfaction and operational continuity.
- Spearhead analyses to improve resource utilization efficiency, identifying and eliminating inefficiencies across infrastructure usage, resulting in cost savings and optimized performance.
- Establish data frameworks that empower support teams to troubleshoot and resolve product issues faster, decreasing response times and enhancing customer experience and support quality.
- Mentor and manage a team of data scientists, instilling best practices in data science, engineering, and fostering a collaborative environment focused on innovative, scalable infrastructure solutions.
What we look for:
- 10+ years of infrastructure data science, machine learning, advanced analytics experience in high velocity, high-growth companies
- 5+ years of management experience hiring and developing teams
- Experience developing data science, analytics, and machine learning and AI products and capabilities in a cloud environment
- Knowledge of statistics and rigorous analytical techniques
- Experience with data visualization tools, knowledge of data engineering, data modeling, and big data technologies
- Leadership skills and experience to lead across functional and organizational lines
- Strong communication skills to explain and evangelize analytics and data science to executives and the senior management team
- Bias to action and passion for delivering high-quality data solutions
- A passion for problem-solving and comfort with ambiguity
- MS or Ph.D. in quantitative fields (Statistics, Math, CS or Engineering)
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.
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 click here.
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.
