Senior Data Engineer

About Legal 500:

Legal 500 was founded by John Pritchard in 1987 as the original clients’ guide to law firms, the first of its kind. It is now a data-driven, AI-optimised research platform which benchmarks, informs and connects providers and users of legal services in over 100 countries worldwide.

Our research and data are trusted and relied upon by corporate clients globally as an essential part of the process, both of instructing law firms with new mandates, and when reviewing existing mandates or panels.

We exist to empower both buyers and sellers in the international legal marketplace to make better decisions and have improved outcomes for their organisations. This is achieved by leveraging a trusted, comprehensive research process with a unique, vast, proprietary and constantly updated set of client-supplied data, unrivalled in the market.

On the supply side of the legal market, every year Legal 500’s team of over 150 researchers, technologists, data analysts, journalists and content specialists collate and review 60,000+ data-submissions from law firms and conduct interviews with thousands of leading law firm partners. On the demand side, Legal 500 analyses confidential data from 300,000+ commercial law firm clients to benchmark law firms and lawyers by practice area; industry; jurisdiction; as well as by proprietary client satisfaction metrics, NPS®, and other qualitative and quantitative criteria.

Legal 500 is the only source of this depth of global research and data on law firms, lawyers and their clients.

Job Summary:

We’re looking for an experienced and forward-thinking Senior Data Engineer to take ownership of the architecture, design, implementation, and optimisation of our enterprise data platform. You will work across our entire data suite from ingestion through transformation to presentation, with a particular focus on Snowflake and dbt.

This is a hands-on role for someone who thrives in a modern, cloud-native environment, enjoys collaborating across disciplines, and isn’t afraid to challenge the status quo to deliver scalable, future-proof solutions.

Key Responsibilities

Architecture & Design

• Lead the design of scalable, secure, and high-performance Snowflake data warehouse solutions.
• Define and enforce best practices in data architecture, including modelling, metadata management, naming conventions, and data lineage.
• Promote a single source of truth approach for all data products and analytics.
• Collaborate with enterprise architects, developers, BI analysts, and data scientists to deliver integrated data solutions.

Development & Integration

• Build and maintain robust ETL/ELT pipelines using dbt, Azure Data Factory, Azure Functions, Python scripts, and other orchestration tools.
• Design and develop complex SQL queries, stored procedures, and views in Snowflake.
• Integrate Snowflake with cloud platforms (Azure, GCP) and other systems via APIs and connectors.
• Support and enhance CI/CD workflows using GitHub Actions, Snowpipe, and other automation tools.
• Work with external vendors or partners involved in data projects.

Performance Optimisation

• Proactively monitor and optimise Snowflake performance (query tuning, warehouse sizing, resource usage, partitioning, clustering).
• Recommend and implement architectural changes to address performance bottlenecks before they impact users.

Security & Compliance

• Implement data governance, access control, and security policies across Snowflake environments.
• Ensure solutions comply with internal standards and relevant regulations.
• Establish quality assurance protocols to validate data accuracy and consistency.

Leadership & Mentorship

• Mentor junior engineers, share expertise, and promote knowledge exchange within the team.
• Contribute to architectural standards, reusable design patterns, and documentation to ensure long-term maintainability.
• Play an active role in building a collaborative, modern data platform culture.

Our Ideal Candidate

We’re seeking someone with the technical depth to design and deliver world-class data engineering solutions, combined with the curiosity, initiative, and team focus to thrive in a dynamic environment.

Must-have technical expertise

• Extensive hands-on experience with Snowflake (architecture, optimisation, advanced SQL).
• Proven dbt experience for data transformation and modelling.
• Strong SQL skills (complex queries, stored procedures, performance tuning).
• Proficiency in Python for automation, scripting, and integration.
• Solid understanding of data modelling techniques (e.g., Kimball method) and metadata management.
• Experience with Azure services (Data Factory, Functions) and APIs/connectors for integration.

Highly valued experience

• Familiarity with data visualisation tools (e.g., Power BI, Tableau) to understand downstream consumption.
• Knowledge of governance frameworks, access controls, and security best practices.
• Experience implementing and advocating best practices, naming standards, and maintainable design patterns.
• Background in environments where systems and processes are evolving and require creative solutions.

Key attributes & behaviours

• Curiosity & innovation – actively seeks opportunities to improve processes, tooling, and architecture.
• Proactive ownership – designs and proposes end-to-end solutions with minimal instruction.
• Collaboration – works closely with peers in development, BI, and data engineering to deliver integrated results.
• Adaptability – comfortable pivoting quickly as priorities or technologies change.
• Best practice advocate – committed to clean, well-documented, and maintainable solutions that minimise technical debt.

Other information:

Hybrid working: 3 days per week in our Fleet Street, London office, 9 am–5 pm.

We value diversity of thought and experience, and encourage applications from all backgrounds.