Senior Data Engineer

As a Senior Data Engineer, you'll play a key role in building and evolving a cutting-edge forecasting platform, helping teams across National Grid access high-quality data and make smarter, more informed decisions.

Working within a collaborative, cross-functional development team, you'll design and build scalable, end-to-end data pipelines that bring together large and complex datasets from multiple sources. Using agile ways of working and strong engineering principles, you'll ensure our data is reliable, accessible and ready to power forecasting, analytics and reporting.

You'll also have the opportunity to help shape the future of our data engineering capability, modernising our architecture, tools and ways of working to improve scalability, performance and speed of delivery.

This is an exciting opportunity for an innovative engineer who is passionate about data, data quality and modern technology, and wants to build solutions that make a real impact at scale.

National Grid is hiring a Senior Data Engineer. This role operates under a hybrid working model and is open to candidates based in either our Waltham, MA, Brooklyn, NY or Hicksville, NY office locations. Hybrid work expectations are subject to business needs and company policy.

• Design, build and support scalable data pipelines, ensuring they are robust, well-tested and ready to meet growing business needs.
• Build and evolve data integrations and APIs, enabling us to manage increasing volumes and complexity of data.
• Champion data quality and governance, ensuring data is secure, consistent, reliable and accessible across the organisation.
• Develop scalable data solutions that align with our architectural roadmaps and standards across data integration, storage, reporting and analytics.
• Partner with analytics and business teams to improve data models, increase accessibility and enable better, data-driven decision making.
• Design and enhance data integration and quality frameworks, supported by strong unit, integration and functional testing.
• Build and automate distributed data solutions that collect and process streaming events from multiple sources.
• Investigate and resolve complex data issues, using data analysis to identify root causes and deliver effective solutions.
• Guide and mentor junior engineers, sharing best practice around coding, engineering standards and optimisation.

You'll be an experienced Data Engineer who enjoys solving complex problems, working with large-scale data and building high-quality solutions that make data easier to access and use.

We'd love you to bring:

• Strong experience in data engineering, analytics or business intelligence, ideally with around 5 years' relevant experience.
• Strong programming skills, particularly Python, alongside hands-on experience with PySpark and SQL.
• Strong experience working with Databricks and building scalable data solutions.
• Experience designing and developing integrations across multiple systems and APIs.
• Hands-on experience with Azure data technologies, such as Azure Data Lake, Azure Data Factory, Azure DevOps and Azure Functions.
• Strong SQL expertise, including working with and optimising queries across large-scale, complex datasets.
• Experience with data warehousing and developing ETL and/or ELT pipelines.
• An understanding of Agile software development methodologies and modern engineering practices.
• Excellent problem-solving and troubleshooting skills, with a structured and process-driven approach.
• Strong documentation skills and a focus on creating maintainable, well-engineered solutions.
• A degree or equivalent experience, ideally within Computer Science, Mathematics, Statistics or another technical discipline.

It would be great if you also have:

• Experience designing data schemas and working with SQL and NoSQL databases.
• Knowledge or experience with Kafka, Flink, Fivetran or Matillion.
• Exposure to Data Science and Machine Learning.
• A background in software engineering.
• Experience working with Snowflake.

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