Location: We operate a flexible, hybrid working environment with the candidate required to travel to either our Winchester or London office once or twice a week. We offer • Competitive Salary • 10% bonus • 6% pension contribution • Private Medical • 25 days annual leave • Access to our comprehensive flexible benefits including discounts on big brands, wellness and employee assistance programmes, gymflex, buy and sell annual leave, travel and dental insurance • Work. Life. Smarter. Our commitment to a flexible and hybrid working culture Purpose We’re looking for a hands-on Principal Data Engineer to lead the design and development of scalable, secure cloud-based data platforms and pipelines that power enterprise analytics, reporting, and real-time decision-making. This is a strategic and technical leadership role, ideal for someone with deep expertise in AWS, Databricks, Apache Spark, and Python/SQL, who can mentor teams, influence architecture, and deliver end-to-end data solutions across a modern tech stack. Accountabilities • Design and deliver enterprise-scale data architectures on AWS using services like S3, EMR, Glue, Redshift, Lambda, and IAM. • Build and manage robust ETL/ELT pipelines supporting both batch and real-time data ingestion and transformation. • Deploy and optimise Apache Spark jobs, leveraging Databricks and Delta Lake for distributed data processing. • Lead the implementation of unified analytics workflows, integrating Databricks with the wider AWS environment. • Write clean, efficient, and reusable code in Python, building production-ready data transformation scripts. • Develop complex SQL queries across multiple RDBMS and cloud-native warehouses. • Drive data quality, lineage, and governance standards across structured and unstructured datasets. • Collaborate with data scientists, analysts, and business stakeholders to define and deliver scalable solutions. • Provide technical mentorship and thought leadership to data engineers and wider delivery teams. • Promote automation and operational efficiency through CI/CD, containerisation (e.g. Docker/ECS), and infrastructure as code. Skills • Python, SQL, PySpark, Scala, Java • AWS (S3, Glue, Redshift, Lambda, EMR, IAM, ECS, SageMaker), Databricks, Delta Lake • Apache Spark, Airflow, Dagster, Rundeck • Kafka, Logstash, NiFi • PostgreSQL, Oracle DB, MongoDB • ELK Stack (Elasticsearch, Logstash, Kibana), Dynatrace, CloudWatch • GitLab, CI/CD, Docker, Infrastructure as Code • Agile/Scrum Knowledge & Experience • Senior/principal data engineering roles with hands-on leadership experience. • Proven success in designing and deploying cloud-native data solutions, particularly on AWS. • Advanced experience with Apache Spark, Databricks, and real-time data processing. • Strong capability in writing and optimising complex SQL and Python code. • Background in handling large-scale data transformations and integrating multiple data sources. • Experience with data lakes, Delta Lake, and modern analytics platforms. • Skilled in stakeholder engagement, mentoring engineers, and delivering high-quality solutions in fast-paced environments. • A passion for simplifying complex problems and building future-proof data infrastructure.