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Applying technology for a better planet
Lead Data Engineer
Location
United Kingdom
Posted
73 days ago
Salary
0
Seniority
Senior
Job Description
Lead Data Engineer
Aqovia
• Act as Chapter Lead for Data Engineering, providing technical leadership, mentoring, and guidance across the data engineering community. • Set and uphold engineering standards, best practices, and ways of working. • Take ownership and accountability for the quality, maintainability, and scalability of data engineering solutions. • Design, develop, modernise, and test data engineering pipelines, including ETL/ELT processes, reports, and data visualisations. • Build and maintain robust real-time and batch data pipelines to meet evolving client and business needs. • Load and transform customer data into target platforms using scalable and reusable patterns. • Implement data management and integration solutions using APIs. • Write complex, performant T-SQL queries and high-quality Python code. • Ensure solutions are well-documented, reusable, maintainable, and production-ready. • Apply source control best practices using Git and contribute to CI/CD pipelines. • Elicit, analyse, and refine multi-stakeholder requirements, translating business needs into technical solutions. • Act as a client-facing consultant, confidently engaging with technical and non-technical stakeholders. • Collaborate closely with internal teams and client stakeholders to provide technical leadership and delivery assurance. • Support pre-sales and sales activities where required, including solution shaping and technical input.
Job Requirements
- Strong experience designing, building, testing, and deploying data pipelines on the Azure platform.
- Advanced T-SQL and Python development skills.
- Proven experience with Git and working within source-controlled, CI/CD-driven environments.
- Expertise in Data analytics platforms (such as Hadoop, Data Bricks or Azure Synapse), Columnar data formats (e.g., Parquet, ORC, Arrow, etc), on-prem to cloud migrations, and both SQL and NoSQL data stores.
- Strong knowledge of batch and real-time data pipeline architectures, including event streaming.
- Experience in data deduplication, transformation, and conformance from source to target structures.
- Solid understanding of logical and physical data modelling and storage design.
- Ability to address observability, data governance, privacy, and architectural concerns.
- Comfortable working autonomously while adopting new tools and technologies quickly.
Benefits
- Competitive benefits package: including healthcare, paid for gym membership, pension scheme, perkbox and more.
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