Lead Data Engineer

Job Description

Lead Data Engineer

Position
Senior Data Engineer to lead and drive forward complex and high-impact data initiatives.

Summary of the Role
Howden Group Services is expanding its internal data engineering capability and is looking for a highly experienced Senior Data Engineer with deep expertise in Databricks and Azure data services. The ideal candidate will have a strong background in designing and delivering scalable, metadata-driven data solutions, particularly in metadata ingestion and orchestration processes.

The role requires a strategic thinker who can lead technical design discussions, drive best practices, and mentor junior engineers. The successful candidate will be comfortable managing multiple deliverables, working closely with stakeholders, and implementing robust data solutions to enable business insights and operational efficiencies.

Responsibilities
The successful candidate will:

• Lead the development of metadata ingestion frameworks and orchestration processes.

• Design and implement scalable and reusable metadata-driven services to optimise data pipelines.

• Architect and maintain robust data solutions using Databricks and Azure services (such as Autoloader, Spark Declarative Pipelines  Azure Data Factory (ADF), Azure Functions, and Azure Data Lake Storage (ADLS)).).

• Establish and enforce best practices for data engineering, CI/CD pipelines, and DevOps for data.

• Collaborate with business stakeholders, data scientists, and analysts to understand data needs and translate them into efficient engineering solutions.

• Optimise and enhance existing data pipelines for performance, reliability, and scalability.

• Drive the adoption of data governance and security best practices.

• Lead the design and maintenance of ETL processes 

• Mentor and support junior engineers, sharing best practices and driving a culture of continuous improvement.

Requirements
Candidates should have:

• 8+ years of experience in data engineering with a strong focus on Databricks (SQL & PySpark).

• Extensive experience with Azure data services, including ADF, ADLS, and Azure Functions.

• Proven track record of designing and implementing metadata-driven data pipelines.

• Deep expertise in orchestration and data workflow automation e.g. Airflow, DBT.

• Strong understanding of CI/CD practices for data engineering.

• Experience with infrastructure as code (Terraform, Bicep, or ARM templates) (preferred).

• Solid development and coding standards, with experience in software engineering best practices.

• Experience leading technical design discussions and driving architectural decisions.

• Strong stakeholder management skills, with the ability to translate business requirements into data solutions.

• Knowledge of data governance, security, and compliance best practices.

• Experience working with insurance data (not essential, but preferred).

This role is an excellent opportunity for an experienced Data Engineer who wants to take on a leadership role, influence best practices, and drive high-impact data initiatives in a modern Azure-based data ecosystem.