Design and develop scalable cloud-based data pipelines and infrastructure. Collaborate with cross-functional teams to ensure high-quality, reliable, and accessible data for analytics and AI/ML capabilities. Ensure data platforms support business needs and emerging technologies.
Key Highlights
Technical Skills Required
Benefits & Perks
Job Description
Job Title: Data Engineer
Salary: £60,000 + Bonus
Location: Fully Remote (UK-based)
Overview
We are seeking an experienced Data Engineer to join our Data team and play a key role in developing scalable, cloud-based data pipelines and infrastructure. This role will support the organisation’s growing data strategy by ensuring high-quality, reliable, and accessible data for analytics, reporting, and future AI/ML capabilities.
The ideal candidate will have strong expertise in Azure, Databricks, and Python, with a proven track record of building and maintaining modern data platforms. Experience in financial services is beneficial but not essential.
Key Responsibilities
Data Architecture & Engineering
- Design, build, and maintain scalable Azure-based data architectures.
- Develop high-performance data pipelines and transformation workflows using Databricks and Python.
- Ensure data platforms support analytics, business intelligence, and emerging GenAI/ML needs.
Pipeline Development & Workflow Management
- Develop, optimise, and monitor ETL/ELT pipelines across various data sources.
- Implement data validation, governance, quality assurance, and security best practices.
- Maintain and improve data lakes, warehouses, and integration layers.
Cross-Functional Collaboration
- Work with analysts, BI teams, and stakeholders to understand data needs and translate requirements into technical solutions.
- Act as a key technical contact for data engineering within the organisation.
- Ensure data models and pipelines effectively support reporting and decision-making.
Performance & Continuous Improvement
- Monitor system and pipeline performance, ensuring SLAs are met.
- Evaluate and implement new technologies and tools to improve data capabilities.
- Automate and streamline processes to enhance scalability and efficiency.
Qualifications & Experience
Essential
- 4+ years of experience in Data Engineering or cloud-based data roles.
- Strong expertise in Azure cloud services and Databricks.
- Advanced proficiency in Python and SQL for data engineering.
- Experience with ETL/ELT tools and orchestration frameworks (e.g., Airflow, dbt).
- Strong knowledge of data warehousing and cloud-based data architectures.
- Understanding of BI tools such as Power BI or Tableau.
- Strong problem-solving and debugging skills.
- Ability to communicate technical concepts to both technical and non-technical audiences.
- Comfortable working independently in a remote environment.
Desirable
- Experience in financial services or public-sector data environments.
- Knowledge of data governance, security, and privacy best practices.