Lead Data and Analytics Engineer

This role is analytics engineering led, with responsibility for ensuring the Silver and Gold layers of the platform are delivered to a consistently high standard, are reliable in production, and meet business needs. You’ll work closely with architects, product and delivery partners, and senior stakeholders, while remaining close enough to the detail to ensure quality, manage risk, and support your team effectively. As our Lead Data & Analytics Engineer, you’ll have access to a wide range of benefits including:

• Mostly remote working, with one day per month in our Leeds Holiday House
• Annual pay reviews
• A generous discretionary profit share scheme
• The opportunity to shape analytics engineering delivery and standards at scale

What you’ll be doing:

• Your primary focus is solutions delivery and team effectiveness, ensuring analytics engineering outcomes are delivered predictably, safely, and to a high standard.
• Leading the delivery of analytics ready data solutions, with a strong focus on quality, reliability, and fitness for purpose primarily across Silver and Gold data layers
• Developing and leading a high performing analytics engineering team, setting clear expectations around capability, standards, quality, delivery discipline, and professional growth
• Providing hands on technical leadership through risk based mentoring, design support, and code reviews, ensuring complex changes are implemented safely and consistently
• Maintaining a keen eye on detail across analytics transformations, identifying delivery risks early and taking action to address them
• Ensuring analytics engineering best practices are followed, including testing, documentation, deployment discipline, and operational readiness
• Working closely with solution and data architects to ensure platform and ingestion decisions support downstream analytics requirements
• Collaborating with data engineering teams on ingestion and orchestration from a range of sources (databases, flat files, APIs, and event driven feeds), while keeping analytics outcomes central
• Acting as the escalation point for production analytics data assets, supporting issue resolution, root cause analysis, and continuous improvement
• Supporting recruitment, onboarding, and ongoing development of analytics and data engineers
• Helping drive a data first culture, promoting shared ownership, learning, and continuous improvement across the data community, * Lead a high performing analytics engineering team, not just manage one
• Own solutions delivery, balancing pace with quality and risk management
• Stay technically credible through design input, reviews, and mentoring
• Influence how analytics data is built, trusted, and operated at scale
• Work with a modern stack: AWS, Snowflake, dbt, Airflow, SQL, and Python

• Strong background in analytics engineering, with experience delivering complex transformations using SQL first approaches, ideally with dbt
• Delivery focused analytics engineering leader who combines technical depth, attention to detail, and people leadership.
• Proven experience understanding, reviewing, and guiding implementation of complex data models across staging (Silver) and warehouse/data mart (Gold) layers
• Advanced SQL capability, with confidence reviewing, optimising, and assuring the quality of complex transformations
• Experience working with a modern cloud data warehouse, ideally Snowflake, or alternatives such as BigQuery, Redshift, or Synapse
• Experience working in a cloud environment (AWS, GCP, or Azure), with exposure to services such as cloud storage and orchestration
• Demonstrable experience leading and developing engineers, supporting capability growth, motivation, and consistent delivery standards
• Experience working in an Agile delivery environment (Scrum and/or Kanban), with strong stakeholder communication skills

Desirable:

• Experience overseeing or supporting data ingestion pipelines, including APIs and event driven data sources
• Familiarity with orchestration tools such as Airflow and modern ELT architectures
• Experience governing or implementing data CI/CD pipelines (e.g. dbt tests, deployment pipelines, automated checks). We currently use Azure DevOps
• Working knowledge of Python for analytics engineering or enablement purposes
• A strong interest in data quality, observability, and operational excellence