Data Engineer

About Pirical

Pirical pioneers the field of People Analytics within the legal industry. Our mission is to help law firms make better, faster and more informed decisions by turning complex people data into actionable insights.

Today, many of the world's leading law firms use Pirical, including all five Magic Circle firms. We are an organically grown business of nearly 50 exceptionally talented team members and have built two market-leading SaaS products over the last decade.
We've grown year on year without external funding, established ourselves as the leader in legal People Analytics in the UK, and are now expanding our products and team internationally.

Why join Pirical?

We asked our team what defines Pirical's culture. In their own words:

“You’re not just a number. You have a voice and can make an impact. It’s extremely rare if you have a good idea here that it won’t be given due diligence. The company will support you to bring them to fruition with a good level of guidance and support.” - Analyst

“HUGE amounts of autonomy and flexibility in a less structured environment than a big company.” - Customer Success Rep

“The company values logic and continuous improvement. Problem-solving from first principles is normal and encouraged.” - Data Engineer

“Ample L&D opportunities. It’s a place where the brighter you want to shine, the company is likely to help facilitate that.” - Software Engineer

The role...

We're looking for a Data Engineer to help transform how Pirical's data operations work.

This role is particularly suited to a Data Engineer with around 3-5 years' experience who is ready for more ownership and wants to start progressing towards technical leadership.

Today, many of the processes that keep our data products running are manual or semi-automated. They work, but we know there's a better way. Your job is to find it. You'll get hands-on with our existing data operations, understand how and why they work, identify where time is being lost and progressively turn manual processes into reliable, observable and automated systems.

You won't simply inherit an established pipeline, pick up tickets and make incremental changes. You'll be expected to understand problems, decide how they should be solved and take ownership of implementing the solution.

As you develop your understanding of our systems, you'll also start to become a technical point of reference within the team - reviewing work, helping less experienced colleagues and raising the engineering standards behind how our data operations run.

For someone who's built strong Data Engineering foundations and is now asking “what's the next step?”, this is an opportunity to take on broader ownership today with a genuine path towards technical leadership as the function develops.

Role Responsibilities...

• Run and maintain Pirical's existing data operations and processing workflows
• Understand existing processes and identify opportunities to make them faster, cheaper and more reliable
• Automate manual and semi-manual data processing pipelines using Python, SQL and appropriate tooling
• Build monitoring, alerting and data quality checks to maintain the integrity of Pirical's data
• Investigate and resolve operational data issues when processes fail or produce unexpected results
• Improve existing scripts and systems so processes can run reliably with less manual intervention
• Design automation that is maintainable, observable and usable by the wider team
• Use AI tooling, including Claude, to improve the speed and quality of operational engineering work
• Review technical work and increasingly help guide more junior members of the team
• Help raise technical and engineering standards across Data Operations
• Work across both day-to-day operational KTLO work and longer-term automation and improvement projects

Role Requirements...

• You'll likely have around 3–5 years' experience in Data Engineering and have reached the point where you're ready to take ownership beyond an individual pipeline or set of engineering tickets.
• Has strong Python and SQL skills and uses them confidently to solve real operational problems
• Experience with AWS, Data Operations, operational engineering or modernising legacy data processes would be beneficial, but isn't essential.
• Has experience building, maintaining and improving production data pipelines
• Has personally identified a manual or inefficient process and built something better to replace it
• Thinks beyond simply getting code to work considering reliability, monitoring, failure states and maintainability
• Can independently investigate data or system failures and logically work towards the root cause
• Wants to own problems end-to-end, rather than simply completing predefined engineering tickets
• Is comfortable working with existing, imperfect systems and improving them progressively
• Naturally looks for opportunities to make systems and processes more efficient
• Is beginning to demonstrate leadership behaviours — whether that's reviewing work, supporting junior colleagues, owning technical decisions or becoming the person others turn to for help
• Wants their next role to give them a route towards technical leadership, rather than simply another Data Engineer position
• Is curious about AI tooling and interested in how tools such as Claude can improve the way they work

Our commitment to diversity

Pirical is committed to being an inclusive and diverse place to work. The excellent work produced at Pirical would not be possible without bringing together all of the different backgrounds, experiences and skills that our team has. We treat every employee equally and fairly regardless of age, disability, gender, marital status, race, religion or sexual orientation. It is vitally important that each of our team members feels confident, comfortable and empowered.

Note to recruitment agencies: Pirical is committed to building a long-term approach to our hiring strategy and is already working in partnership with selected talent partners. We therefore ask you to hold off sending speculative CVs or sales approaches.