We are looking for a skilled Senior Data Engineer (Analytics) to play a key role in building and scaling a modern, cloud-based data platform for a fast-growing, technology-driven organisation.
This role sits at the intersection of data engineering and analytics, with a strong emphasis on designing robust data pipelines, developing high-quality datasets, and enabling self-service analytics across the business.
You will help shape a scalable data ecosystem that empowers teams to make data-driven decisions through accessible, reliable, and well-structured data. The environment prioritises simplicity, maintainability, and scalability, leveraging cloud-native tooling and configuration-driven approaches over complex custom builds.
Working across AWS and Azure, you will contribute to a modern data platform incorporating cloud data lakes, warehouses, and BI tools, supporting both internal analytics and customer-facing data solutions.
Key Responsibilities
- Design, build, and maintain scalable data pipelines using modern ELT frameworks (e.g. Azure Data Factory, Airflow or similar)
- Develop and optimise analytics-ready datasets to support reporting, operational insights, and downstream applications
- Work with a variety of data sources including APIs, relational databases, and semi-structured data stores
- Improve and maintain existing Python-based data workflows and orchestration processes
- Ensure data pipelines are robust, efficient, and support incremental processing
- Monitor, troubleshoot, and optimise pipeline performance and query efficiency
- Support and enable self-service analytics by delivering well-structured, trusted datasets
- Collaborate with engineering, product, and business teams to define and deliver data requirements
- Contribute to data architecture decisions, tooling selection, and platform improvements
- Implement and maintain data governance, security, and access controls (e.g. RBAC)
- Integrate with third-party systems and external data providers via APIs
- Support the delivery of embedded or customer-facing analytics solutions
Skills & Experience
Core Requirements
- Strong experience in a Data Engineering or Analytics Engineering role
- Advanced SQL skills and solid understanding of data modelling principles
- Experience building and maintaining data pipelines in cloud environments
- Strong problem-solving skills with the ability to translate business needs into data solutions
- Experience working with large-scale and/or complex datasets
- Familiarity with performance tuning and optimisation across data pipelines and queries
- Strong communication skills and ability to work cross-functionally
Technical Experience (examples)
- Cloud Platforms: AWS and/or Azure
- Data Storage & Processing: Data warehouses, data lakes, and databases (e.g. Redshift, Snowflake, BigQuery, S3, Azure Data Lake)
- ELT / Orchestration Tools: Azure Data Factory, Apache Airflow, AWS Glue, Matillion or similar
- Programming: Python (or similar for data processing and orchestration)
- BI & Visualisation: Power BI, Tableau, or similar tools
- Data Types: Structured and semi-structured data (e.g. JSON, document stores)
- Experience with data security and access control frameworks (e.g. RBAC, identity providers)
- Experience integrating external APIs and third-party data services
- Exposure to regulated or data-sensitive environments
- Experience evaluating and selecting data tools and vendors
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