Job description

Who are our employees? We’re an eclectic group of 5,000+ dreamers, believers and builders, operating in over 40 countries. We’re Hungry. Humble. Honest. With Heart. The 4H’s: these are our core values and the DNA of our company. They help drive our employees to succeed, to strive to be better, to learn from every experience. Our employees are encouraged to have spirited debates and conversations and to think with a founder’s mindset. This means we’re all CEO’s of the company and, as such, make the best decision every day that aligns with our company goals. It’s through our values, our conversations and mindsets that we can continue to disrupt the industry and drive innovation in the market. Who are we in the market? Nutanix is a global leader in cloud software and hyperconverged infrastructure solutions, making infrastructure invisible so that IT can focus on the applications and services that power their business. Companies around the world use Nutanix Enterprise Cloud OS software to bring one-click application management and mobility across public, private and distributed edge clouds so they can run any application at any scale with a dramatically lower total cost of ownership. The result is organizations that can rapidly deliver a high-performance IT environment on demand, giving application owners a true cloud-like experience. Learn more about our products at www.nutanix.com or follow us on Twitter @Nutanix . removed=====---> Hungry, Humble, Honest, with Heart. The Opportunity Are you a visionary leader with a passion for transforming data into actionable insights, and a track record of building and inspiring high-performing analytics teams? If so, joining our team as a Senior Manager, Analytics Engineering at Nutanix will allow you to make a meaningful impact by influencing data-driven decision-making across the organization and driving the development of innovative analytics solutions in a collaborative and dynamic environment. About the Team At Nutanix, the Data Analytics team is a dynamic group of over 50 collaborative and innovative professionals spread across the US and India. This diverse team consists of data scientists, analysts, and engineers who work together to drive insights and enhance decision-making through data-driven strategies. The culture within the team fosters open communication, encourages fresh ideas, and values each member's contribution, making it an exciting environment for those passionate about analytics and technology. You will report to the Sr. Director of Data Analytics, who prioritizes mentorship and professional development while leading a supportive team environment. This position is a hybrid role, requiring you to work in the office for three days a week at our headquarters in San Jose, CA, providing the opportunity to collaborate in person with your colleagues while also allowing for flexibility. Travel requirements for this role are minimal, ensuring you can focus on your work without frequent disruptions. Your Role • Set the vision and direction for enterprise analytics engineering and inspire teams around trusted, scalable, and intelligent analytics. • Build, lead, and develop a high-performing team of analytics engineers and data professionals. • Create a culture of ownership, collaboration, curiosity, technical excellence, and continuous learning. • Serve as a trusted advisor to business and technology leaders by deeply understanding business processes, priorities, KPIs, and decision needs. • Translate complex requirements into semantic models, certified datasets, reusable metrics, and governed analytical data products. • Lead by example through hands-on SQL development, dimensional modeling, data validation, reconciliation, technical design, and solution reviews. • Design and implement trusted semantic layers that standardize business definitions, KPI logic, dimensions, measures, hierarchies, and reusable business rules. • Build scalable analytical models and transformations using SQL, dbt, Python, Spark, or similar technologies. • Establish strong engineering practices for architecture reviews, testing, documentation, certification, deployment, and lifecycle management. • Implement data quality, metadata, lineage, ownership, reconciliation, and governance controls. • Partner across Data Engineering, Governance, AI, BI, and distributed analytics teams in a hub-and-spoke operating model. • Implement practical AI and GenAI capabilities, including natural-language querying, semantic search, automated insights, SQL assistance, and conversational analytics. • Ensure AI-enabled analytics is grounded in trusted datasets, governed semantic models, approved KPIs, and secure access controls. • Coach and mentor team members while raising the technical and process maturity of the broader analytics community. What You Will Bring • 10+ years of experience in Analytics Engineering, Data Engineering, Business Intelligence, Data Analytics, or Enterprise Analytics. • 5+ years leading analytics engineering teams, enterprise analytics initiatives, or cross-functional analytics delivery. • Demonstrated experience building, coaching, and inspiring high-performing technical teams. • Expert-level SQL with strong hands-on experience in dimensional modeling, semantic layers, certified datasets, analytical transformations, and data products. • Proven ability to understand complex business processes and translate them into trusted KPIs, semantic models, and governed analytical products. • Strong business acumen and experience defining enterprise KPIs with business stakeholders. • Experience with platforms such as Snowflake, Databricks, BigQuery, Redshift, or Postgres. • Experience with dbt, Spark, Python, Airflow, or similar analytics engineering technologies. • Strong understanding of data quality, reconciliation, metadata, lineage, governance, and certification. • Hands-on experience implementing AI or GenAI-enabled analytics solutions. • Excellent communication and influencing skills, with the ability to build trust and align business and technology teams. Preferred Qualifications • Experience in SaaS, enterprise software, technology, or other data-intensive environments. • Experience supporting domains such as GTM, Finance, Customer Success, Marketing, Product, Operations, or Supply Chain. • Experience with Salesforce, NetSuite, Workday, SAP, Coupa, Clari, Zuora, or similar platforms. • Experience operating within a hub-and-spoke analytics model. Work Arrangement Hybrid: This role operates in a hybrid capacity, blending the benefits of remote work with the advantages of in-person collaboration. In locations where our workplace policy applies (i.e. San Jose, Durham, Mexico City, Bangalore, Pune, Hoofddorp, Belgrade, Barcelona, Singapore, Sydney and Tokyo), employees are expected to work onsite a minimum of 3 days per week to foster collaboration, team alignment, and access to in-office resources. Workplace type may vary based on location and team requirements. Please speak with your recruiter for details. Additional team-specific guidance and norms will be provided by your manager. The pay range for this position at commencement of employment is expected to be between USD $ 184,000 and USD $ 368,000 per year. However, base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. The total compensation package for this position may also include other elements, including a sign-on bonus, restricted stock units, and discretionary awards in addition to a full range of medical, financial, and/or other benefits (including 401(k) eligibility and various paid time off benefits, such as vacation, sick time, and parental leave), dependent on the position offered. Details of participation in these benefit plans will be provided if an employee receives an offer of employment. If hired, employee will be in an “at-will position” and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors. Our application deadline is 40 days from the date of posting. In good faith, the posting may be removed prior to this date if the position is filled or extended in good faith. --

Requirements

Must-haves

Who are our employees?
Who are we in the market?
removed=====--->
Hungry, Humble, Honest, with Heart.
About the Team
Set the vision and direction for enterprise analytics engineering and inspire teams around trusted, scalable, and intelligent analytics.
Build, lead, and develop a high-performing team of analytics engineers and data professionals.
Create a culture of ownership, collaboration, curiosity, technical excellence, and continuous learning.
Serve as a trusted advisor to business and technology leaders by deeply understanding business processes, priorities, KPIs, and decision needs.
Translate complex requirements into semantic models, certified datasets, reusable metrics, and governed analytical data products.
Lead by example through hands-on SQL development, dimensional modeling, data validation, reconciliation, technical design, and solution reviews.
Design and implement trusted semantic layers that standardize business definitions, KPI logic, dimensions, measures, hierarchies, and reusable business rules.
Build scalable analytical models and transformations using SQL, dbt, Python, Spark, or similar technologies.
Establish strong engineering practices for architecture reviews, testing, documentation, certification, deployment, and lifecycle management.
Implement data quality, metadata, lineage, ownership, reconciliation, and governance controls.
Partner across Data Engineering, Governance, AI, BI, and distributed analytics teams in a hub-and-spoke operating model.
Implement practical AI and GenAI capabilities, including natural-language querying, semantic search, automated insights, SQL assistance, and conversational analytics.
Ensure AI-enabled analytics is grounded in trusted datasets, governed semantic models, approved KPIs, and secure access controls.
Coach and mentor team members while raising the technical and process maturity of the broader analytics community.

Nice-to-haves

Experience in SaaS, enterprise software, technology, or other data-intensive environments.
Experience supporting domains such as GTM, Finance, Customer Success, Marketing, Product, Operations, or Supply Chain.
Experience with Salesforce, NetSuite, Workday, SAP, Coupa, Clari, Zuora, or similar platforms.
Experience operating within a hub-and-spoke analytics model.
Work Arrangement

Application prep

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sqlpythonaipostgres

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Benefits

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Vision

401(K)

Paid Time Off

Parental Leave

Professional Development