Permanent | Hybrid Working | South East England We are partnering with a fast-paced, customer-focused organisation undertaking a significant data transformation programme. With major investment in a modern lakehouse platform and access to rich, high-volume datasets, this is an opportunity to help reshape how data is stored, analysed and leveraged across the business. As a Senior Platform Data Engineer, you will provide technical leadership within the Data Engineering team, working closely with Data Scientists, Machine Learning Engineers and business stakeholders to deliver scalable, high-value data solutions. Key Responsibilities - Design and build robust, scalable data pipelines to serve analytics and data science communities - Provide hands-on expertise across modern data engineering technologies (e.g. Databricks, Spark, Python, SQL, Scala) - Collaborate with data scientists and ML engineers to develop and deploy machine learning models addressing key business challenges - Coach and mentor engineers (including contractors), raising development standards and engineering maturity - Partner with Business Analysts to translate requirements into measurable business outcomes - Oversee code quality and project deliverables across releases - Establish and maintain documentation libraries and data catalogues for developed products - Contribute to platform evolution and continuous improvement of data engineering practices Core Skills & Experience Technical Capability - Significant experience designing and delivering data solutions on cloud-based, distributed big data platforms - Strong hands-on software engineering experience in Python, with knowledge of modern development practices (TDD, CI/CD, automated deployment pipelines) - Experience with automated testing of data transformation pipelines (e.g. Pytest, dbt unit testing frameworks) - Strong SQL skills, including performance tuning and debugging - Experience in data warehouse optimisation (schema evolution, indexing, partitioning) - Infrastructure as Code experience (e.g. Terraform or CloudFormation) - Strong knowledge of distributed data processing frameworks such as Apache Spark (or similar technologies such as Flink, Hadoop or Beam) - Familiarity with lakehouse architecture principles and modern data platforms - Experience implementing data quality, lineage and observability frameworks - Understanding of data governance, security and privacy principles, including handling of sensitive data within regulated environments Engineering & Collaboration - Comfortable working independently while aligning with overarching data strategy - Strong communication skills across technical and non-technical audiences - Structured, analytical problem-solver with a focus on outcomes and innovation - Passionate about modern data technologies and continuous learning Desirable Experience - Experience building real-time or event-driven data pipelines in commercial production environments (e.g. streaming architectures, Kafka, Spark Streaming, Beam) - Understanding of unbounded data processing and streaming design patterns - Familiarity with machine learning workflows and model lifecycle considerations - Experience supporting analytical visualisation tools (e.g. Tableau, Power BI or similar platforms) - Experience working within airline, ecommerce, retail or similarly data-rich industries - Experience within AWS cloud environments - Experience building transformation frameworks using dbt