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Reporting directly to the EVP of Engineering and Technology the Head of Data Engineering will lead and manage a team of engineering managers across multiple product engineering squads focused on delivering innovative data-centric products. You'll be responsible for
defining and driving the data platform strategy using Azure Cloud technologies, overseeing the
development of data infrastructure, data pipelines, and data products with a strong emphasis on
security, scalability, governance, and business impact. You'll collaborate with cross-functional teams, align with business goals, and ensure the successful
delivery of high-impact data products and systems.
Requirements
Leadership & Team Management:
- Lead and mentor a team of 6+ Tech Leads overseeing product engineering squads
delivering data-centric products.
- Provide strategic guidance, coaching, and professional development opportunities
for engineering managers to empower their teams and deliver results.
- Establish and maintain a high-performance culture focused on collaboration,
innovation, and continuous improvement.
- Foster a culture of mentorship and leadership development, identifying and
nurturing talents
o Drive the recruitment, retention, and development of top-tier engineering talent
within the data engineering team.
Drive Data Platform Strategy & Implementation:
- Define and drive the overall data platform strategy with a focus on Azure Cloud to
ensure that the organization’s data infrastructure is scalable, reliable, and aligned
with business objectives.
- Oversee the design, implementation, and ongoing optimization of the data platform,
leveraging Azure technologies such as Azure Data Factory, Azure Synapse
Analytics, Azure Data Lake, and Azure SQL Database.
- Ensure the data platform supports data engineering, analytics, and data science
initiatives across squads.
- Ensure the data platform enables easy access to high-quality, secure, and
compliant data for all stakeholders, fostering a self-service analytics environment.
Cross-Squad Coordination & Alignment:
- Ensure alignment across multiple squads to meet company-wide data objectives
and maintain strategic coherence.
- Facilitate collaboration between product management, data science, analytics, and
engineering teams to deliver data-driven products and services.
- Define shared goals, success metrics, and timelines for squads to ensure that
efforts are aligned with broader business goals.
Data Strategy & Architecture:
- Develop and execute the data engineering strategy, ensuring alignment with the
company’s overall business objectives.
- Oversee the design and implementation of scalable, reliable, and secure data
architectures to support various data products and services.
- Ensure adherence to best practices for data governance, security, and compliance
across the engineering squads.
- Stay at the forefront of industry trends and emerging technologies, continually
improving data engineering capabilities.
Metrics-Driven Impact:
- Develop and track success metrics, including data pipeline reliability, availability,
and time-to-insight, to evaluate and continuously improve team performance.
- Communicate the impact of data engineering initiatives through clear metrics to
stakeholders at all levels.
Operational Excellence & Process Improvement:
- Promote operational excellence through the implementation of efficient data
engineering workflows, processes, and tools.
- Drive the adoption of best practices for data pipeline development, continuous
integration/continuous deployment (CI/CD), and data monitoring.
- Identify and implement opportunities for automation and optimization, improving
operational efficiencies across squads.
Innovation & Technology Leadership:
- Champion the exploration and adoption of new tools, technologies, and frameworks
to improve the effectiveness of data engineering processes and product
development.
- Influence the evolution of the company’s data architecture to support emerging
needs and business growth, including machine learning and AI-based solutions.
- Lead efforts to modernize and scale the data infrastructure, ensuring flexibility for
future needs.
Stakeholder Communication & Reporting:
- Communicate the status, strategy, and outcomes of data engineering initiatives to
senior leadership and other stakeholders.
- Translate complex technical challenges and opportunities into clear business terms
for non-technical audiences.
o Track and report on key performance indicators (KPIs), providing regular updates on
the health and impact of data engineering initiatives.
Resource & Project Management:
- Oversee financial planning, budgeting and controling for the data engineering
organization (CAPEX, OPEX)
- Lead the prioritization and allocation of resources across engineering squads,
ensuring alignment with business priorities and timely delivery of high-impact
projects.
- Balance short-term needs with long-term strategic goals, ensuring that data
engineering efforts are sustainable and scalable.
- Oversee the management of project timelines, budgets, and deliverables, ensuring
successful execution of data product initiatives.
Benefits
- This is a remote role where you’ll be trusted to work with autonomy and impact.
- Participation in our annual Incentive Plan (VIP) Company bonus scheme
- 25 days annual leave plus bank holidays
- Option to buy and sell up to 9 days annual leave
- Access to voluntary benefits including private medical insurance, cycle to work scheme, subsidised gym membership
- Automatic inclusion in Life Assurance, Critical Illness and Disability Income protection schemes
- Pension scheme up to 8% employer contribution
- Access to reward & discount platform
- Wellbeing initiatives
- Volunteering day
We reserve the right to bring forward the closing date of our job vacancies if we receive a suitable number of high-quality applications from which to make a shortlist. We recommend that you apply for our roles as soon as possible rather than wait until the published closing date