Elastic - Sr. Director, Enterprise Data
Requirements
• 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. • 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. • 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. • Competitive pay based on the work you do here and not your previous salary • Health coverage for you and your family in many locations • Ability to craft your calendar with flexible locations and schedules for many roles • Generous number of vacation days each year • Increase your impact - We match up to $2000 (or local currency equivalent) for financial donations and service • Up to 40 hours each year to use toward volunteer projects you love • Embracing parenthood with a minimum of 16 weeks of parental leave
Responsibilities
• 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. • 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. • 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. • 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.
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