Senior Data Engineer I

Job Description

Would you like to be part of a team that delivers high-quality software to our customers

Are you a highly visible champion with a ‘can do’ attitude and enthusiasm that inspires others

About the Business

At Data Services, our goal is to keep the world connected. We are a leading provider of analytics, helping customers understand the past, present, and predict what comes next.

As part of our strategic evolution, we are investing in a shared, central data and AI platform designed to enable teams across the organisation to build trusted, reusable, and scalable data capabilities. Foundry standardises the foundations of how data is ingested, governed, transformed, and delivered, allowing product and domain teams to focus on differentiated value

About the Role

This role is focused on designing and delivering high-quality, production-ready data and software solutions within a modern, platform-enabled environment. You will work across systems and teams to translate business needs into scalable, reliable, and reusable data capabilities.

As part of our transition to a more platform-driven operating model, you will contribute to building data products that can be reused across teams and use cases, rather than one-off pipelines. You will collaborate closely with domain teams and platform services to ensure solutions align with shared standards, governance, and delivery patterns.

The role also operates within an evolving ecosystem where contract-driven data approaches are increasingly used to define datasets, structure, quality expectations, and access patterns. While direct experience with data contracts is not required, exposure to structured data governance, schema ownership, or similar concepts would be beneficial.

You will be expected to design across multiple systems and markets, and engage directly with stakeholders to shape solutions that are robust, scalable, and aligned to long-term platform direction.

About the Team:

Our teams operate in cross-functional squads, bringing together engineering, product, and analysis capabilities as a Data Platform Engineering team. We work as the core platform team supporting multiple markets in their business-critical Data platform and shared capabilities.

Responsibilities

• Design, develop, test, and deploy production-ready applications and data pipelines using Python, PySpark, and related technologies

• Build and maintain scalable data solutions that align with shared platform patterns and can be reused across multiple use cases

• Collaborate with cross-functional teams to gather and translate business requirements into robust, scalable technical designs

• Design and implement data models, transformation pipelines, and ETL processes, ensuring data integrity, performance, and scalability

• Contribute to the development and adoption of standardised engineering practices, including CI/CD, code reviews, and automated testing

• Debug and resolve complex production issues, ensuring high-quality and resilient systems

• Work with platform capabilities (e.g., data storage, orchestration, governance tooling) to deliver solutions aligned to organisational standards

• Participate in Agile delivery processes, including stand-ups, sprint planning, and reviews

• Contribute to improving reusable patterns, pipelines, and engineering approaches, helping reduce duplication and increase delivery speed across teams

Requirements

• Bachelor’s degree in Computer Science, Software Engineering, or related analytical field, or equivalent practical experience.

• 5–7 years of professional software engineering experience, with strong hands-on coding expertise.

• Advanced proficiency in Python, PySpark, and ETL development, including data manipulation and optimization techniques.

• Working knowledge (basic to intermediate) of AWS, Airflow, Snowflake, Iceberg, SQL, Linux, Docker, GitHub, Terraform, Excel.

• Strong understanding of data modeling concepts (normalized and dimensional models) and multiple data storage systems.

• Advanced knowledge of software development methodologies (Agile, Waterfall) and industry best practices.

• Experience with test-driven development (TDD), complex bug resolution, and writing detailed technical specifications.

• Strong analytical, research, communication, and collaboration skills, with the ability to work effectively with internal and external technical teams.

Learn more about the LexisNexis Risk team and how we work here









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