The Data Engineering Manager is responsible for establishing and overseeing the Data Engineering and Data Ops functions, ensuring the efficient and effective management of data to drive business value.
Develop and own the data engineering strategy and roadmap to maximize long-term business value.
Prioritize, plan, and ensure the timely and high-quality delivery of data engineering initiatives.
Oversee third-line support, technology upgrades, and the introduction of new technologies within agreed timelines.
Provide technical guidance and mentorship to the team and wider organization on data engineering challenges and solutions.
Design and architect scalable data pipelines for efficient data ingestion, transformation, and loading.
Manage and optimize data platforms, including infrastructure, upgrades, and connectivity.
Build and lead a high-performing Data Engineering team, including internal staff and third-party resources.
Establish clear service definitions, SLAs, and performance expectations for the team, ensuring adherence.
Act as a data and analytics champion, fostering a culture of innovation and excellence within the Analytics & Insight team.
Stay abreast of industry trends and emerging technologies to enhance data infrastructure and capabilities.
Manage budgets for data-related activities and projects within the broader analytics budget.
Establish and manage third-party commercial agreements, including vendor selection and contract negotiations.
Collaborate with stakeholders across functions to align data engineering initiatives with business goals.
Leverage a deep understanding of the business and data landscape to drive value through data initiatives.
Degree or equivalent qualification in a data-related discipline or relevant experience in high-performing Data Engineering and Analytics functions.
Proven leadership experience in managing Data, Environment, and Release Delivery teams, including resource and cost management.
Expertise in Data Engineering and Environment management, preferably in AWS, with experience in automation tools.
Strong knowledge of SQL & Python, with hands-on experience in data engineering tools and technologies.
Experience working on data science and machine learning projects.
Familiarity with Data Ops or DevOps environments and software development life cycles.
Strong team development and performance management skills.
A positive leader with a growth mindset, striving to build a high-performing data function.