9 months ago
Birmingham, United Kingdom or London, United KingdomStaff+
Responsibilities
- Design and develop data-processing and data-persistence software components for systems handling data at scale.
- Own development of complete components or subsystems, including design, coding, testing, defect resolution, integration, and due diligence.
- Design, implement, and optimize ETL/ELT data-processing pipelines with attention to robustness, performance, and operational readiness.
- Define and enforce development standards, style guides, automation, deployment practices, and testing approaches.
- Lead troubleshooting, tuning, unit testing, and integration testing activities.
- Work with architects, Operations teams, Security Architects, accreditors, customers, managers, and other engineers on technical and operational requirements.
- Estimate effort and explain technical implications for user stories and user journeys.
- Contribute to technical proposals as part of the sales process.
- Manage, coach, and develop a small number of staff, including performance management and career development.
Requirements
- Experience leading a team of engineers implementing data-intensive system components.
- Experience applying design, development, and operational-readiness standards, including patterns, style guides, automation, and deployment.
- Proficiency in software development with Java, Scala, or Python.
- Experience with data-processing platforms such as Informatica, Azure Databricks, or other relevant ETL tools.
- Expertise in SQL or SQL extensions for analytical use cases.
- Expert understanding of distributed data stores and data-processing frameworks.
- Proficiency designing analytical and operational data models.
- Ability to communicate technical designs clearly in writing and verbally.
- A keen interest in AI technologies.
- Desirable experience with data warehouse methods and techniques.
- Desirable AWS, Azure, or GCP certification in data services.
- Desirable practical experience with AI technologies, tools, processes, and delivery.
- Experience contributing to continuous improvement, data best practices, and development or technology communities.
Benefits
- People-first culture with support for professional growth and development.
- Inclusive workplace committed to diversity, equity, inclusion, accessibility, and recruitment accommodations.
Categories
Data Engineering
