Data Engineer

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.

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