Senior Engineer, Data Engineering
1 day ago
Ensure technical resiliency of all data integration solutions and services
- Support the delivery of ongoing data engineering activities
- Enhance and support existing data product outputs for both internal and external customers.
- Collaborate with technical colleagues across the organisation to design robust data integration solutions
- Demonstrate excellent, sustainable and collaborative software development practice that’s focused on delivering highly readable, maintainable and appropriate artefacts.
- Actively participate in all team events, leading where specialist knowledge is required and supporting the team to improve their process through inspection and adaptation.
- Engage with the wider communities of practice and interest to share knowledge, technique and experience Requirement for Data Engineering services
- Ensures high quality of developed solutions through development and maintenance of unit tests - with appropriate code coverage - and code analysis using code quality tools,
- Ensure that developed software complies with non-functional software requirements such as accessibility, security, UI/UX, performance, maintainability and deployability.
- Routinely use collaborative development practices such as pairing and mobbing techniques in programming, code reviews, system design and requirements analysis, etc.
- Support and deliver the disaster recover assurance of digital services, striving towards a sustainable Recovery Time Objective of 2hrs and Recovery Point objective of zero. This will be assured at 6 weekend points over the course of a FY year.
Python
- PostgreSQL
- Modern DevOps and CI/CD practices and tooling including Docker, GitLab CI, AWS CodePipeline, AWS CDK and AWS CloudFormation
- Expertise in SQL, data transformation and analysis
- Delivering high quality software collaboratively in high-performing, cross functional development teams.
- Experience implementing data ETLs, data streaming systems and data integration solutions
- Experience working in the Agile delivery models - such as Scrum and/or Kanban frameworks.
Data warehousing
- Hybrid on-premises/cloud solutions
- AWS Glue, Step Functions, Lambda functions, S3, RDS, Data Migration Service
- Using testing tools for unit testing, including system test automation frameworks
- PostGIS for PostgreSQL
- Monitoring, alerting, intelligence tools and processes, including Grafana
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