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For Companies At a Glance
- Tasks: Build and optimise data platforms, ensuring quality and reliability in a collaborative environment.
- Company: Join Legal 500, a leader in the global legal market with a focus on data excellence.
- Benefits: Enjoy hybrid working, competitive salary, and opportunities for professional growth.
- Other info: Be part of a dynamic team in a supportive culture, located in vibrant Fleet Street, London.
- Why this job: Make a real impact by shaping data engineering standards and solving complex challenges.
- Qualifications: Strong SQL, Snowflake, and Python skills with a passion for data quality and integrity.
The predicted salary is between 60000 - 80000 £ per year.
At Legal 500, data sits at the heart of how we support and inform the global legal market. As we continue to scale our data platform and expand the use of trusted analytics across the business, we’re looking for a Senior Data Engineer to help build the foundations that ensure our data is accurate, reliable, observable, and trusted by default. This is not a role focused purely on moving data from A to B. We’re looking for an engineer who genuinely cares about data quality, testing, integrity, monitoring, and operational excellence, someone who enjoys solving complex platform challenges and building scalable engineering standards that other teams can rely on. You’ll join a growing Data team within a Microsoft/Azure environment and play a key role in shaping how data engineering is done across the business.
What We’re Looking For
- Strong SQL and Snowflake expertise, including designing, optimising, and testing analytical data models, alongside implementing data validation and integrity checks.
- Strong Python engineering experience within modern data environments, including automation, pipeline development, and operational tooling.
- Proven experience implementing data quality and testing frameworks across modern data stacks, including schema testing, anomaly detection, reconciliation checks, and dbt/CI/CD integration.
- Experience working with Infrastructure as Code principles and tools such as Terraform or similar.
- Experience implementing monitoring, alerting, observability, and orchestration solutions using tools such as Dagster, GitHub, and CI/CD workflows.
What Success Looks Like
- Data quality issues are detected automatically and early.
- Failures are visible, actionable, and monitored effectively.
- Engineers and analysts trust the data platform by default.
- Testing and validation become embedded into everyday engineering workflows.
- The platform scales confidently as data usage and business demands increase.
Location & Working Pattern: Fleet Street, London Hybrid working – 3 days per week in the office.
Senior Data Engineer employer: Legal 500
Contact Detail:
Legal 500 Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who might have insights into Legal 500. A friendly chat can sometimes lead to opportunities that aren’t even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving SQL, Python, and data quality frameworks. This gives potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for the interview by brushing up on common data engineering challenges. Be ready to discuss how you’ve tackled issues related to data integrity and monitoring in past roles. We want to see your problem-solving skills in action!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at Legal 500.
We think you need these skills to ace Senior Data Engineer
Some tips for your application 🫡
Show Your Passion for Data: When you're writing your application, let us see your genuine interest in data quality and integrity. Share examples of how you've tackled complex data challenges in the past and why you care about building reliable data systems.
Highlight Your Technical Skills: Make sure to showcase your strong SQL and Python expertise. We want to know about your experience with Snowflake and any data validation frameworks you've implemented. Be specific about your technical achievements and how they relate to the role.
Demonstrate Your Problem-Solving Abilities: We love engineers who enjoy solving problems! In your application, mention instances where you've improved data processes or implemented monitoring solutions. This will show us that you’re not just about moving data but also about enhancing its quality.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about our company culture and values.
How to prepare for a job interview at Legal 500
✨Know Your Data Inside Out
Before the interview, make sure you brush up on your SQL and Snowflake skills. Be ready to discuss how you've designed and optimised analytical data models in the past. They’ll want to hear about specific challenges you faced and how you ensured data quality and integrity.
✨Showcase Your Python Prowess
Prepare to talk about your experience with Python in modern data environments. Highlight any automation or pipeline development projects you've worked on. It’s a great opportunity to demonstrate how you’ve implemented operational tooling that enhances data workflows.
✨Emphasise Quality-First Mindset
This role is all about data quality, so be ready to discuss frameworks you've implemented for testing and validation. Share examples of how you’ve used schema testing, anomaly detection, or reconciliation checks to ensure data reliability. They’ll appreciate your commitment to operational excellence.
✨Familiarise Yourself with Infrastructure as Code
Since they’re looking for someone experienced with tools like Terraform, make sure you can explain how you've applied Infrastructure as Code principles in your previous roles. Discuss any monitoring and orchestration solutions you've implemented, especially if they relate to CI/CD workflows.