Data Engineering Manager

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.

Key Responsibilities

• 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.

Required Expertise

• 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.

Key Competencies & Attributes

• Strong team development and performance management skills.
• Ability to coach and motivate teams under pressure and manage competing priorities.
• A commitment to continuous learning and staying up to date with evolving technologies.
• Attention to detail, fairness, and integrity.
• Inquisitive and innovative mindset, with a drive to explore new processes and methodologies.
• Excellent communication and collaboration skills, with the ability to engage stakeholders across business functions.
• A positive leader with a growth mindset, striving to build a high-performing data function.
• Strong decision-making and problem-solving capabilities.
• Ability to balance business objectives with resource constraints and competing priorities.