Lead Data Engineer

real-time analytics.Write and review high-quality, production-grade code in Python, SQL, and IaC (Terraform) that sets the standard for engineering excellence.Design and deliver end-to-end data pipelines.Optimise performance, reliability, and cost-efficiency across all data workflows and systems.Lead development of Superscript’s MLOps capabilities, ensuring seamless model deployment, monitoring, and feedback loops.Own and improve data quality frameworks and observability to ensure trust in business-critical data assets.Produce detailed technical documentation accessible to both technical and non-technical stakeholder s.Lead complex, high-impact data initiatives from concept through to delivery, including scoping, architecture, resource planning, and execution.Anticipate risks, identify dependencies, and clearly communicate trade-offs between speed, quality, and business impact.Drive platform automation and resilience, ensuring rapid, reliable delivery of new data features and models.Lead

coach and support Data Engineers and Analytics Engineers, creating an environment where individuals can grow in confidence, capability and impact.Provide structured feedback and guidance through code reviews, pair programming, and knowledge-sharing sessions.Collaborate with Product Managers, Analysts, and stakeholders to design impactful data products that advance business goals.Foster a culture of experimentation, continuous improvement, and technical curiosity within the data functio n.About you:Deep understanding of modern data architectures (data lakehouse, event-driven pipelines, and orchestration systems).Strong proficiency in Python, SQL, and IaC (Terraform).Experience using dbt, Snowflake, AWS, orchestration tool like Prefect.Experienced in building and maintaining batch and streaming data pipelines at scale.Skilled in managing and optimising cloud infrastructure for cost and performance.Knowledge of CI/CD, testing frameworks, version control (Git), and containerisation

(Docker/Kubernetes).Strong background in data modelling, warehousing, and supporting analytical and ML workloads.Exposure to MLOps tools including MLFlow, kedro and Amazon Sagemaker.Development and maintenance of real time products like APIs using FastAPI/Flask.Operates autonomously with strong ownership and accountability.Strategic thinker who balances immediate delivery with long-term platform evolution.Excellent communicator who can bridge technical and business domains.Collaborative leader who uplifts others through mentorship, clarity, and support.Passionate about continuous improvement, technical excellence, and innovation in data engineering.In return, we offer you:A competitive salary and the ability to grow your career25 days holiday - so there’s plenty of time for work, rest and playHybrid way of working for the perfect work / life balanceVitality private health and dental insuranceAdded benefits including competitive pension and salary sacrificeAccess to financial wellbeing platform MintagoFull access to Spill , our mental health platformCycle to work schemeFun andmodern office environment with regular team social events #J-18808-Ljbffr

As Lead Data Engineer at Superscript, you’ll be the technical and strategic owner of our data platform, the foundation that powers everything from business intelligence and underwriting models to machine learning predictions and data products.You’ll define and drive the evolution of our modern data ecosystem to ensure it’s robust, scalable, and efficient. Working closely with stakeholders across Data, Tech, and the wider business, you’ll lead the design and delivery of data solutions that underpin our ability to understand and serve customers, manage risk intelligently, and make data-driven decisions at scale.You’ll also act as a mentor and technical leader within the team, up-skilling others, setting engineering standards, and ensuring our data capabilities continue to be a strategic differentiator for Superscript.What you’ll get up to:Define the architectural vision for Superscript’s data platform, ensuring it scales with our business and supports diverse use cases including BI, ML, and