Senior Manager, Infrastructure Data Science

Databricks · Mountain View, California · Engineering · listed November 18, 2024

The shape of it

Seniority
Manager
Experience asked
5+ years
Where
Not stated
Stated pay
$228,600 – $314,250 USD
Requirements listed
10
Length
864 words

In the posting’s own words

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.

What it asks for · 10

  • 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)

What the job covers

  • 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.

Degree language

  • MS or Ph.D. in quantitative fields (Statistics, Math, CS or Engineering)

Tools and skills named

Data
  • Databricks5×
  • Spark2×
  • Statistics2×
  • Data modeling
Models & research
  • Machine learning2×
Security & compliance
  • Security2×
Go to market
  • SaaS

Words the posting leans on

  • data18×
  • infrastructure10×
  • data science7×
  • engineering7×
  • experience7×
  • customer4×
  • solutions4×
  • world4×
  • analytics3×
  • data-driven3×
  • performance3×
  • products3×
  • support3×
  • challenges2×
  • customer experience2×
  • data scientists2×

Counted from the posting after the mission statement and the legal notices are set aside. The ones near the top are the ones a screener is looking for.

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How this page was made

An automated read of a public job posting, fetched August 24, 2026 and last changed by Databricks on August 18, 2026. Every list above is pulled from the posting’s own sentences — nothing rewritten, nothing added, no judgment about the role or the company. Counts and seniority are read off the text by rule, so they can be wrong where the posting is unusual. The original is the only thing that binds. Openings close without warning; check the source before spending an evening on it.