Sr. Director, Enterprise Data

Skills this role screens for

About the role

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI.

What is The Role

We are seeking a visionary and execution-focused Senior Director of Enterprise Data to lead the transformation and maturity of our data ecosystem. Having recently scaled to $2 billion in annual revenue, we are actively building the infrastructure, governance, and operational models required to sustain our trajectory to $4 billion and beyond.

In this role, reporting to the CIO, you will own the end-to-end data strategy, evolving our data platform architecture, scaling our Master Data Management (MDM) systems into an active operational hub, and institutionalizing federated data governance. You will bridge the gap between complex engineering and business execution, transforming data from a utility into a high-octane product that powers real-time decision-making, predictive analytics, agentic AI and operational efficiency across the global enterprise.

The work

What You Will Be Doing

Also

Data Strategy & Platform Evolution

• Architect the Future: Design, execute, and evolve a scalable data platform roadmap capable of handling a multi-billion dollar enterprise’s volume, velocity, and variety of data.
• De-bottleneck Legacy Infrastructure: Transition our centralized pipelines into a modern, decoupled data architecture.
• Data as a Product: Implement a "Data as a Product" mindset across engineering teams, ensuring datasets have strict Service Level Objectives (SLOs), rigorous uptime, and high catalog discoverability.
• Streaming & Real-Time Analytics: Drive the evolution from purely batch-oriented processing to real-time event streaming for critical business domains like Engineering, Finance, and Customer Experience.

Also

Enterprise Master Data Management (MDM)

• Build the Golden Record: Evolve our current cross-referenced registry into a highly integrated, multi-domain operational MDM hub (Customer, Product, Vendor/Supplier).
• Operational Syncing: Ensure mastered data seamlessly flows bidirectionally between analytic environments and core operational execution systems (ERP, CRM, eCommerce).
• M&A Readiness: Standardize ingestion frameworks to quickly harmonize data from future acquisitions or new business units without interrupting daily operations.

Also

Data Governance, Quality, & Compliance

• Federated Governance: Establish an enterprise-wide data governance council. Move governance away from gatekeeping and toward a collaborative data stewardship model owned by business units.
• Automated Observability: Implement modern, automated data lineage, cataloging, and quality testing tools to monitor data health and proactively catch pipeline degradation before it hits business dashboards.
• Security & Compliance: Partner with Security and Legal teams to ensure the enterprise data platform natively adheres to global regulatory frameworks (GDPR, CCPA, SOX) through robust RBAC/ABAC and automated data masking.

Also

Team Leadership & Operating Model

• Scale the Organization: Restructure and grow a high-performing data team consisting of data engineers, MDM specialists, platform architects, and data governance managers.
• Centralized Infrastructure, Embedded Analytics: Champion a hub-and-spoke operating model, providing a central platform layer while enabling embedded data analysts within business units to move fast safely.
• Cultivate Data Ops: Instill software engineering rigor into data workflows, including CI/CD deployment pipelines, infrastructure-as-code, and comprehensive automated test suites.

Who they want

What You Bring

• Proven Scale Experience: Minimum of 12+ years of progressive leadership in data engineering, data architecture, or enterprise data management, with explicit experience inside an organization operating in a B2B environment at a $1B to $5B+ revenue scale.
• Architectural Fluency: Deep hands-on and strategic familiarity with modern cloud data stacks (e.g., Snowflake, Databricks, BigQuery, AWS/Azure data suites) and enterprise MDM platforms (e.g., Informatica, Reltio, Semarchy, Profisee).
• Change Management Mastery: Documented success in leading complex corporate data migrations or massive MDM implementations across multi-business-unit enterprises.
• Business Acumen: Ability to translate complex technical jargon into clear business value, financial ROI, and strategic alignment for C-suite executives.
• People Leadership: Minimum of 5 years managing manager-level and architect-level direct reports, with a track record of hiring, mentoring, and retaining top-tier engineering talent.

Nice to have

Bonus Points

Compensation for this role is in the form of base salary. This role does not have a variable compensation component.

The typical starting salary range for new hires in this role is listed below. In select locations (including Seattle WA, Los Angeles CA, the San Francisco Bay Area CA, and the New York City Metro Area), an alternate range may apply as specified below.

These ranges represent the lowest to highest salary we reasonably and in good faith believe we would pay for this role at the time of this posting. We may ultimately pay more or less than the posted range, and the ranges may be modified in the future.

An employee's position within the salary range will be based on several factors including, but not limited to, relevant education, qualifications, certifications, experience, skills, geographic location, performance, and business or organizational needs.

Elastic believes that employees should have the opportunity to share in the value that we create together for our shareholders. Therefore, in addition to cash compensation, this role is currently eligible to participate in Elastic's stock program. Our total rewards package also includes a company-matched 401k with dollar-for-dollar matching up to 6% of eligible earnings, along with a range of other benefits offered with a holistic emphasis on employee well-being.

The typical starting salary range for this role is:

$212,100—$335,600 USD

The typical starting salary range for this role in the select locations listed above is:

$254,900—$403,200 USD

Additional Information - We Take Care of Our People

As a distributed company, diversity drives our identity. Whether you’re looking to launch a new career or grow an existing one, Elastic is the type of company where you can balance great work with great life. Your age is only a number. It doesn’t matter if you’re just out of college or your children are; we need you for what you can do.

We strive to have parity of benefits across regions and while regulations differ from place to place, we believe taking care of our people is the right thing to do.…

• Experience navigating fast-paced, high-growth environments characterized by rapid organizational restructuring or frequent Mergers & Acquisitions (M&A).
• Expertise in setting up a Data Mesh or federated data architecture in a hybrid or multi-cloud environment.
• Active engagement or understanding of integrating AI/ML infrastructure readiness into core enterprise data platforms.