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 to hire an experienced Senior/Lead Data Engineer to lead on the architecture, design, implementation, and optimisation of our enterprise data architecture using Snowflake from ingestion to presentation.
About the role:
We see this role as being broad in remit, across our entire data suite. Below is a summary of the types of stuff you'll be tackling.
Architecture & Design:
* Lead the design of scalable, secure, and high-performance Snowflake data warehouse solutions
* Define and implement data architecture best practices, including data modeling, metadata management, and data lineage
* Collaborate with enterprise architects, BI teams, and data scientists to deliver integrated data solutions
Development & Integration:
* Design and develop complex SQL queries, stored procedures, and views in Snowflake
* Build and manage robust ETL/ELT pipelines using tools like Azure Data Factory
* Integrate Snowflake with cloud platforms (Azure, GCP) and other systems via APIs and connectors
* Work with external vendors or partners involved in data projects
Performance Optimisation:
* Monitor and optimise Snowflake performance, including query tuning, warehouse sizing, and resource usage
* Implement data partitioning, clustering, and caching strategies for efficient querying
Security & Compliance:
* Implement data governance, access control, and security policies across Snowflake environments
* Ensure data architecture supports compliance with regulations
* Implement quality assurance protocols to validate data accuracy, consistency, and compliance with internal standards
Leadership & Mentorship:
* Mentor junior engineers and participate in code and design reviews
* Contribute to team knowledge sharing, training sessions, and architectural standards
Our ideal candidate:
* Extensive experience in Snowflake
* Strong knowledge of data modelling techniques (e.g. Kimball method)
* Proficiency with data visualization tools (e.g., Power BI, Tableau) and scripting languages (e.g., Python).
* Knowledge of the likes of SQL, R, Juypter notebooks and Streamlit
* Understanding of data governance and metadata standards
Other information:
This role is hybrid, with 3 days a week in our Fleet Street office in central London
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