Data Engineer (Enterprise DataWarehouse Developer)

As a Data Engineer, you’ll design and maintain data scrapers and data pipelines, design & optimize analytics & relational databases, and build analytics models using DBT and bespoke aggregation engines. You’ll work closely with business stakeholders, other BI Developers and DataOps as well as System engineers to support both data and application integrations using bespoke tools written in Python/Java, as well as tools such as Meltano, Airflow, Mulesoft/Snaplogic, Apache NIFI, and Kafka, ensuring a robust, well-modelled, and scalable data analytics infrastructure running on MySQL and Postgres style databases primarily. 

Requirements

Essential Skills / Experience: 

SQL, Data Modelling & Database Administration 

• Advanced SQL development and deep understanding of RDBMS concepts and engines 

• 5+ years' experience designing dimensional models (Kimball-style stars/Inmon schemas) 

• Practical knowledge of Data Warehouse infrastructure architecture and best practices 

• Practical database design, development, administration knowledge (any RDBMS) 

• Strong understanding of data governance, quality, and privacy (e.g. GDPR compliance) 

Data Transformation & Pipelines 

• Proficiency in ELT/ETL processes 

• Strong experience in data ingestion, transformation & orchestration technology (ETL tools such as Informatica, Datastage, SSIS, etc..) or open source Meltano, Airbyte, and Airflow 

• Proven experience with DBT (data build tool) 

Analytics & Dashboarding 

• Proficiency with business intelligence tools (Power BI, Tableau, SAP BI, or similar). 

Integration & Programming 

• Hands-on experience with API development and integration (REST/SOAP) 

• Proficiency in at least 1 object/procedural/functional language (e.g: Java, PHP, Python) 

• Familiarity with EAI tools such as MuleSoft/SnapLogic or Apache NiFi 

Desirable Skills / Experience: 

• Experience with infrastructure-as-code tools such as Terraform and Ansible 

• Experience with version control (e.g. Git, SVN) and CI/CD workflows for deployment 

• Experience scraping external data sources using Beautiful Soup, Scrapy, or similar 

• Familiarity with Database Replication & CDC technologies such as Debezium 

• Familiarity with message & event-driven architecture, including tools like AWS MQ, Kafka 

• Exposure to cloud database services (e.g., AWS RDS, Snowflake) 

Benefits

• 25 days of holiday
• Bonus
• Pension contribution

• Private medical, dental, and vision coverage
• Life assurance
• Critical illness cover
• Wellness contribution program with access to ClassPass
• Plumm Platform
• Five volunteering days
• Give as You Earn initiative
• Learning and development programs
• Electric Vehicle Scheme
• Cycle to Work Scheme
• Season Ticket Loan