Director, Enterprise Data & Analytics

Posted 4 Hours Ago
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Hyderabad, Telangana, IND
In-Office
Expert/Leader
Software
The Role
Lead Gainsight's enterprise data platform and analytics org: own Snowflake pipelines and SLAs, govern the semantic layer and canonical metrics, run the Data Council, build a certified data catalog, enable self-service analytics, partner with CS/Sales/Finance for domain analytics, and hire/develop platform, analytics, and governance teams in a federated model.
Summary Generated by Built In

We’re building the AI-driven future of customer success, from retention to growth!

We’re building the AI-driven future of customer success, from retention to growth! Gainsight is the AI-powered retention engine behind the world’s most customer-centric companies. The Gainsight CustomerOS platform orchestrates the customer journey from onboarding to outcomes to advocacy. More than 2,000 companies trust Gainsight’s applications and AI agents to drive learning, adoption, community connection, and success for their customers. To explore how our suite of solutions is shaping the future of customer success, check out the link.

About This Role:

We’re looking for a full-time Director, Enterprise Data & Analytics to join our Engineering team reporting to the Chief AI & Transformation Officer . This role is a hybrid role based out of our Hyderabad, India.

In this role, you'll play a key role in giving every function at Gainsight a single, trusted source of data by owning the platform, pipelines, semantic layer, and domain analysts that turn raw data into decisions. This is a great opportunity for someone who thrives in a fast-moving, cross-functional build environment and enjoys working cross-functionally with teams like Customer Success, Sales, GTM, Finance, and Engineering. The ideal candidate brings strong skills in modern data stack architecture (Snowflake, dbt, pipeline orchestration), semantic layer ownership and metric governance, and leading multi-disciplinary data teams.

What You'll Do:

Data Platform & Infrastructure

  • Own the Snowflake architecture, ingestion pipelines, and data reliability SLAs across all business functions.

  • Define and enforce pipeline standards, data quality monitoring, and incident response so every function can trust the data they work with.

  • Partner with Engineering to maintain clean, documented data contracts between source systems (Gainsight CS, Salesforce, RevPro, NetSuite, Workday, Ramp) and the warehouse.

  • Build toward a self-service analytics environment where business teams can access certified data without waiting on a central queue.

Semantic Layer & Metric Governance

  • Own all certified data models and the company’s canonical metric definitions - the authoritative source for ARR, NRR, churn rate, pipeline, health score, headcount, and all other business-critical KPIs.

  • Facilitate the Data Council: the cross-functional governance body where CS, Sales, GTM, Finance, and Engineering align on definitions. When teams disagree on what a number means, the Data Council decides - and the outcome is encoded in code, not a slide deck.

  • Build and maintain the data catalog - the living registry of every certified metric, its definition, source system, owner, refresh cadence, and change history.

  • Drive data literacy across the organization so business teams know how to find, interpret, and trust the data available to them.

Cross-Functional Domain Analytics

  • Partner with domain analysts and stakeholders embedded across CS, Sales, GTM, and Finance - people who sit with their business teams and translate function-specific needs into solutions built on the central platform.

  • Support Customer Success with a reproducible, certified health score model, automated QBR data packages, and churn signal reporting that CSMs actually rely on.

  • Support Finance with clean automated pipelines from RevPro, NetSuite, etc. that eliminate manual close reconciliation and give Finance a trusted month-end workflow.

  • Support Sales & GTM with reliable pipeline, funnel, and attribution data so RevOps and GTM leadership can run forecasting and planning from a single source.

  • Prioritize domain coverage in partnership with the Chief AI & Transformation Officer based on where data gaps are causing the most business impact.

Team & Culture

  • Hire and develop the Enterprise Data & Analytics org: platform engineers, analytics engineers, a governance manager, and domain analysts.

  • Operate a federated model: the central team sets standards, domain analysts execute within them - neither a pure ivory tower nor a fully decentralized free-for-all.

  • Create the conditions for data to be a shared organizational capability, not a scarce resource controlled by one team.

This role may require occasional travel (up to 20%) for team meetings, training, or company events.

This is not a complete list of responsibilities, and the scope of the role may evolve with the needs of the team and business.

What We're Looking For:

Must-have skills or experience:

  • 12+ years in data, analytics, or data engineering, with at least 5 years leading multi-disciplinary data teams.

  • Proven experience building or standardizing a data platform across multiple business functions in a SaaS environment - not just maintaining one someone else built.

  • Strong hands-on fluency with the modern data stack: Snowflake, dbt, a pipeline orchestration tool (Fivetran, Airflow, or equivalent), and at least one BI platform (Sigma, Looker, Tableau, or similar).

  • Experience owning a semantic layer and driving cross-functional alignment on metric definitions — you have brought Finance, Sales, and CS stakeholders to a shared agreement on business-critical KPIs like ARR, NRR, and churn, and ensured that alignment is encoded in governed, production-ready data models rather than remaining an informal understanding.

  • Working knowledge of data governance: cataloging, lineage, access controls, data quality frameworks, and how to make governance feel like enablement rather than bureaucracy.

  • Demonstrated ability to build credibility with non-technical business leaders across CS, Finance, Sales, or GTM and translate data platform capabilities into outcomes they care about.

  • Experience hiring and developing data talent across engineering, analytics, and governance disciplines.

  • Demonstrated curiosity and practical experience applying AI and LLM-based tools to accelerate data workflows - whether automating pipeline documentation, enabling natural language querying across the semantic layer, or surfacing anomalies and data quality issues without manual intervention.

Nice-to-have skills or experience:

  • Hands-on familiarity with the Gainsight data stack (e.g., Gainsight CS, Salesforce, RevPro, NetSuite) and data catalog platforms (e.g., Atlan, Alation, or Collibra).

  • Experience operating in federated or hub-and-spoke data models across multiple business domains (e.g., supporting both CS/RevOps and Finance/FP&A).

  • Exposure to ML/AI applications in a SaaS context (e.g., predictive churn, revenue forecasting) and experience driving company-wide data literacy or self-service analytics programs.

Why You’ll Love It Here:

Gainsight is a place where innovation is shaped through collaboration, curiosity, and a shared focus on solving real-world problems. With a growing suite of products across customer success, product experience, community, education, and AI-powered relationship intelligence, we continue to evolve with the needs of our customers. When people with diverse strengths, a strong sense of community, and true passion for our mission come together, they drive greater impact and create lasting value. What underpins it all is a culture that offers the stability, trust, and support that people need - not just to do the job, but to show up as themselves and feel connected to the work they do. Gainsters love working here for several reasons. Here are a few:

Our Compensation and Benefits: At Gainsight, we believe great work happens when teammates feel fully supported.

  • We offer a comprehensive benefits package including full health coverage (including OPD), wellness and mental health resources, flexible remote work options, and childcare assistance. You'll also enjoy dedicated Recharge Holidays - one long weekend each quarter to relax and reset.


Our Core Values: We are guided by our values and our mission to be living proof you can win in business while being Human-First. Learn more here.

 

Our Growth Opportunities: From mentoring to career development opportunities, we’re passionate about helping our teammates learn, grow, and thrive.

 

Our Parody Videos: No explanation needed. Just watch them here!

 

If this sounds like the right role for you, we’d love to hear from you.

 
 

Additional Information:

We’re committed to creating an inclusive, fair, and transparent hiring process. As an equal opportunity employer, we celebrate diversity and are committed to creating a welcoming experience for all candidates.

If you require accommodations or have questions about how your personal data will be used during the hiring process, please contact [email protected].

If you’re applying for a role through an Employer of Record (EOR) or contractor arrangement, please note that employment terms and benefits are managed by the EOR or may not apply to non-EOR contractors.

Skills Required

  • 12+ years in data, analytics, or data engineering
  • At least 5 years leading multi-disciplinary data teams
  • Proven experience building or standardizing a data platform across multiple business functions in a SaaS environment
  • Hands-on fluency with Snowflake and dbt
  • Experience with a pipeline orchestration tool (Fivetran, Airflow, or equivalent)
  • Experience with at least one BI platform (Sigma, Looker, Tableau, or similar)
  • Experience owning a semantic layer and driving cross-functional alignment on metric definitions (ARR, NRR, churn, etc.)
  • Working knowledge of data governance: cataloging, lineage, access controls, data quality frameworks
  • Demonstrated ability to build credibility with non-technical business leaders across CS, Finance, Sales, or GTM
  • Experience hiring and developing data talent across engineering, analytics, and governance disciplines
  • Practical experience applying AI and LLM-based tools to accelerate data workflows
  • Familiarity with Gainsight CS, Salesforce, RevPro, NetSuite (nice-to-have)
  • Familiarity with data catalog platforms (Atlan, Alation, Collibra) (nice-to-have)
  • Experience operating in federated or hub-and-spoke data models (nice-to-have)
  • Exposure to ML/AI applications in SaaS (predictive churn, revenue forecasting) (nice-to-have)
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The Company
HQ: San Francisco, CA
898 Employees
Year Founded: 2009

What We Do

Gainsight’s innovative customer-centric technology is driving the future of customer success. The company’s Customer Cloud offers a powerful set of solutions focused on customer success, product experience, revenue optimization, customer experience, and customer data, that together enable businesses to put the customer at the center of everything they do.

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