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Data engineer

Milton Keynes
Scania Group
Data engineer
€65,000 a year
Posted: 17 April
Offer description

Location: Milton Keynes

Working Hours: Monday to Friday (8.45am – 5pm)


Benefits

* Salary: From £60,000 plus excellent benefits package, including Hybrid working
* Eligibility to annual bonus scheme
* Access to a fantastic loan car scheme
* 25 days annual leave plus bank holidays
* Competitive pension
* 4x basic salary life assurance


Responsibilities

* Design, develop and maintain data pipelines using Azure Data Factory and Snowflake (ELT approach)
* Implement and manage data structures within Snowflake, ensuring performance, scalability and consistency
* Maintain and optimise data layers (e.g. raw, curated, presentation) aligned to data architecture standards
* Monitor and manage platform performance and cost efficiency
* Develop and maintain integrations across multiple source systems using APIs, file-based and batch processes
* Build reusable frameworks and templates for data ingestion and transformation
* Ensure reliability, resilience and recoverability of all integration processes
* Support onboarding of new data sources into the platform
* Implement data quality checks, validation rules and monitoring processes
* Develop alerting and logging mechanisms for pipeline failures and data issues
* Identify, troubleshoot and resolve data inconsistencies and failures
* Work with upstream system owners to improve data quality at source where possible
* Apply role-based access control (RBAC) and data security best practices within Snowflake
* Ensure compliance with organisational security and data governance policies
* Maintain documentation for data pipelines, data models and integrations
* Support audit and compliance activities where required
* Support administration of the data platform including user access, roles and permissions
* Ensure business continuity, backup and recovery processes are in place and maintained
* Maintain operational stability of data pipelines and infrastructure
* Contribute to the evolution of data engineering standards, frameworks and best practices
* Identify opportunities to improve performance, scalability and maintainability of the platform
* Stay informed of emerging tools, technologies and practices relevant to data engineering
* Work with business stakeholders, analysts and technical teams to understand data requirements
* Support delivery of data solutions aligned to business needs and priorities
* Provide technical input into data-related initiatives and projects
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