Lead Data Engineer

What do we offer in return?

Reasonable adjustments

Qualifications

• 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.
• 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.
• 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.
• What do we offer in return?
• Our successes have all come from someone brave enough to try something new
• We support each other in the small everyday moments and the bigger challenges
• We are determined to make a positive difference at work and beyond
• Reasonable adjustments
• We're committed to providing reasonable accommodations at Howden to ensure that our positions align well with your needs. Besides the usual adjustments such as software, IT, and office setups, we can also accommodate other changes such as flexible hours or hybrid working.
• If you're excited by this role but have some doubts about whether it’s the right fit for you, send us your application – if your profile fits the role’s criteria, we will be in touch to assist in helping to get you set up with any reasonable adjustments you may require.
• Not all positions can accommodate changes to working hours or locations. Reach out to your Recruitment Partner if you want to know more.

Preferred Qualifications

• Experience with infrastructure as code (Terraform, Bicep, or ARM templates) (preferred).
• Experience working with insurance data (not essential, but preferred).

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.