Vice President, Enterprise Data

Darktrace

11d

About The Position

As Darktrace accelerates global growth and product innovation, data becomes mission-critical. The Vice President of Enterprise Data is a strategic, enterprise-wide leadership role reporting to the CIO, with a responsibility for designing, building and maintaining a unified data ecosystem that drives innovation, operational excellence and regulatory compliance. With oversight across the full data lifecycle, the VP of Enterprise Data leads platform strategy, data architecture, data engineering, data management and data governance. The role will partner closely with business leaders, analytics teams, technology and security, to ensure that data is unified and managed as a secure, governed and scalable enterprise asset. The role will ensure that the enterprise data platform is future proofed, cloud native and AI ready, providing the business with the flexibility and scalability to adapt and elevate operational performance at speed and scale.

Requirements

• 15+ years leading enterprise data functions in complex, multi-region tech environments; experience at CDO or VP Data level.
• Deep expertise in cloud-native data platforms, streaming/eventing, metadata/lineage, DataOps, and MLOps, with proven adoption of AI/ML-enabled SDLC and observability.
• Track record in portfolio rationalisation, governance frameworks, and building communities of practice.
• Executive presence; able to advise the CIO/Board and influence across Product, Engineering, and Business.
• Bachelor’s/Master’s in Computer Science, Engineering, Data Systems, or related field.
• Outcome-driven delivery, able to cut through complexity and stabilize in-flight programs.
• Run-Transform-Grow mindset, balance BAU excellence with transformative programs tied to business value.
• Agentic AI & Data Enablement, move from experiments to enterprise-grade impact with ethical governance.
• Executive Storytelling, clarify trade-offs and secure alignment at Board level.

Responsibilities

• Define, own, and execute the enterprise data strategy and multi-year roadmap aligned with the enterprise business priorities and CIO’s technology strategy.
• Establish data as a foundational capability supporting digital transformation, AI adoption, and data-driven decision-making.
• Orchestrate the pathway to data democratization across the business.
• Serve as the senior data leader within IT, advising the CIO and executive leadership on data investments, risks, and opportunities.
• Lead the design, implementation, and evolution of enterprise data architecture across on-premises and cloud environments.
• Oversee architectural design of enterprise data platforms including data lakes, warehouses, streaming platforms, and AI-ready data environments.
• Ensure platforms meet enterprise standards for scalability, resiliency, security, interoperability, and cost management.
• Facilitate simplification and rationalization of data applications and artefacts.
• Build enterprise data platforms and establish enterprise standards for data pipelines, APIs, metadata-driven integration, and real-time data processing.
• Direct enterprise data engineering teams responsible for ingestion, transformation, integration, and delivery of data at scale.
• Enable consistent, secure by design, reusable data products and services across lines of business.
• Implement data governance frameworks, standards, policies, and operating models that enable speed (not bureaucracy) and embed developer friendly pathways.
• Set rules and expectations for data quality, integrity and lineage.
• Define associated SLAs.
• Ensure high levels of compliance, accountability and data ethics.
• Define data ownership and stewardship models in partnership with business and IT leaders.
• Partner with cybersecurity, risk, legal, and compliance teams to ensure adherence to privacy, security, and regulatory requirements.
• Own enterprise data management practices including master data management, reference data, metadata, data lifecycle management, and records retention.
• Operate databases, data lakes and data warehouses, monitoring technical failures and outages.
• Own the tooling, monitoring, quality checking and remediation for data quality and observability.
• Ensure data assets are discoverable, well-documented, and effectively managed across their lifecycle.
• Maintain FinOps practices across the data platform to ensure costs are transparent and fully optimized.
• Ensure data platforms support business intelligence, advanced analytics, machine learning, and generative AI use cases.
• Partner with analytics and AI teams to enable high-quality training and inference data.
• Accelerate AI adoption through improved data readiness and model lifecycle integration.
• Build and scale a global, high-performing data organization with strong succession planning.
• Define operating models between central IT and federated business analytics teams.
• Develop talent, succession plans, and career paths.
• Champion modernisation waves and change management, balancing near-term delivery with long-term simplification.

Benefits

• 23 days’ holiday + all public holidays, rising to 25 days after 2 years of service
• Additional day off for your birthday
• Private medical insurance which covers you, your cohabiting partner and children
• Life insurance of 4 times your base salary
• Salary sacrifice pension scheme
• Enhanced family leave
• Confidential Employee Assistance Program
• Cycle to work scheme

What This Job Offers

• Job Type: Full-time
• Career Level: Executive