Senior Data Engineer

About the role

At Bionic, we're on a mission to make it radically easier to run a small business. As the UK's leading business comparison and switching service, we help thousands of small and medium-sized businesses save time and money on essentials like energy, broadband, insurance, and finance. We combine smart technology with real human support to match our customers with the best deals - quickly and effortlessly. With trusted partnerships including Compare the Market, Uswitch for Business, MoneySuperMarket and Confused.com, we're committed to help SMEs get the best deals for their business essentials every time. The Role As a Senior Data Engineer you'll be responsible for designing, building, and scaling robust, high-quality data platforms that underpin critical business reporting and operational decision-making. You will drive the development of data pipelines, models, and architecture across our modern data stack (AWS, Snowflake, dbt) ensuring performance, reliability, and scalability. Working closely with Architecture, Data Analytics, and Salesforce teams, you will drive the evolution of our data platform, guide best practices, and play a key role in modernising legacy processes. You will act as a technical leader within the team, shaping design decisions, mentoring engineers, and ensuring delivery of resilient, well-governed data products. This role requires strong technical expertise, strategic thinking, and the ability to translate complex business needs into scalable, production-grade data solutions. Key Responsibilities Design, build and optimise scalable data pipelines and data products across AWS, Snowflake and dbt, setting engineering standards and best practices. Lead the development of robust, testable dbt models and frameworks to ensure high data quality, consistency, and maintainability. Own data pipeline reliability, proactively monitoring, troubleshooting, and resolving complex data and performance issues with minimal disruption. Architect and evolve analytics-ready data models (e.g., star schemas, data marts), balancing performance, flexibility, and usability. Collaborate with senior stakeholders (Analytics, Salesforce, Architecture) to define requirements and translate them into scalable technical solutions. Drive continuous improvement of data engineering practices, including CI/CD, observability, testing frameworks, and documentation standards. Provide technical leadership through mentoring, code reviews, and guidance to junior team members, fostering engineering excellence. Ensure compliance with security, governance, and data privacy requirements, embedding best practices in all solutions. Contribute to strategic data platform decisions, including tooling, architecture, and long-term roadmap planning. Essential Skills and Experience required Proven experience designing, building and maintaining scalable data pipelines and cloud-based data platforms in production environments. Advanced SQL expertise, including query optimisation, performance tuning and complex data transformations. Strong Python skills for data engineering, automation and system integrations. Hands-on experience with Snowflake (or similar cloud data warehouse), including data modelling, optimisation and security/access controls. Strong experience with dbt, including modelling, testing and deployment best practices. Solid knowledge of AWS data services and cloud-native architectures (e.g. S3, Lambda, IAM, CloudWatch). Experience with modern software engineering practices, including Git, CI/CD and automated testing. Strong understanding of data modelling and data warehousing principles. Ability to solve complex problems, identify root causes and deliver scalable, reliable solutions. Experience leading technical delivery, influencing architectural decisions and collaborating across multiple stakeholders. Comfortable working in ambiguity, translating complex business requirements into structured technical solutions. Strong communication skills, with the ability to engage both technical and non-technical audiences. Nice to have's Experience with real-time or streaming data architectures. Exposure to Salesforce data models and API integrations. Experience using AWS CDK for infrastructure deployment. Familiarity with orchestration tools such as Airflow. Experience implementing data observability, monitoring and alerting solutions. Knowledge of BI platforms such as Tableau and how data products are consumed by end users. Exposure to MLOps practices, including supporting machine learning pipelines, model deployment and monitoring. Awareness of emerging trends, technologies and best practices within modern data engineering. Why Join Bionic? At Bionic, better never stops. You'll join a team obsessed with improvement, innovation, and impact - where your expertise will directly shape how thousands of British businesses grow and thrive. Benefits We know that our employees are what sets us aside from our competitors; our benefits are just part

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