ABOUT THE COMPANY

We are a global legal technology company that has been building software for the legal industry for over two decades. Our AI-powered cloud platform is used by leading law firms, Fortune 500 corporations, and government agencies worldwide to organise complex data, surface critical insights, and act on them — across litigation, investigations, regulatory inquiries, and data breach response.

We're valued at $3.6 billion and invest over $170 million annually in R&D. We're making substantial investments in data lake technology and distributed systems to support future growth and advanced analytics. Our scale means the data problems here are genuinely hard — and the platforms you build will have real consequence across the organisation.

ABOUT THE ROLE

We're building a specialised team focused on enabling advanced analytics and reporting capabilities across our internal data ecosystem. As a Senior Data Platform Engineer, you'll combine strong software engineering principles with deep data expertise to build robust, cloud-native platforms that process large-scale datasets efficiently and enable internal teams to build reporting and analytics on top of them.

The role emphasises cloud-native architecture, lakehouse integration, data warehousing, and governance best practices. You'll work on systems using Apache Spark, Delta Lake, and Iceberg, and help deliver curated data models and self-service analytics capabilities to internal stakeholders. You'll also participate in on-call rotations as part of shared team responsibility.

WHAT YOU'LL WORK ON

Data pipeline and distributed systems

Design and implement scalable data pipelines and distributed systems using Spark and Python to process and transform large-scale datasets for analytics and reporting.

Lakehouse platform development

Develop and maintain lakehouse capabilities with Delta Lake and Iceberg, ensuring data reliability, versioning, and performance optimisation at scale.

Analytics workflow enablement

Integrate dbt for SQL transformations running on Spark. Collaborate with internal teams to deliver curated datasets and self-service analytics capabilities for reporting and advanced use cases.

Data warehousing optimisation

Integrate and optimise Databricks and Snowflake for scalable storage and query performance. Drive performance tuning and cost optimisation across Spark jobs and cloud-native environments.

Governance and observability

Implement observability and governance frameworks including data lineage, quality checks, and compliance controls. Build platforms that allow secure and compliant access to diverse data sources.

Engineering best practices

Apply and champion clean code, modular design, CI/CD, automated testing, and code review standards across all data engineering work.

On-call participation

Participate in on-call rotations as part of shared team responsibility for platform reliability.

WHAT WE LOOK FOR

Python and SQL

Strong programming skills in both Python and SQL, applied to production data platform work at scale.

Apache Spark

Solid hands-on experience with Spark for distributed data processing, including performance tuning in production environments.

Lakehouse architecture

Expertise in Delta Lake and/or Apache Iceberg. You've applied these in production and understand the trade-offs in real-world scenarios.

dbt and analytics tooling

Practical experience with dbt for transformation workflows. Familiarity with Databricks and Snowflake for large-scale analytics workloads.

Data governance and compliance

Understanding of data governance, lineage tracking, and compliance requirements in large-scale, multi-tenant data environments.

Infrastructure and containerisation

Familiarity with Kubernetes, Docker, and infrastructure-as-code tools in cloud-native environments.

Software engineering fundamentals

Solid understanding of software engineering principles — CI/CD, automated testing, clean code, and modular design applied to data systems.

Bonus

Exposure to event-driven architectures and advanced analytics platforms. Experience enabling self-service analytics for internal stakeholders. Experience in Java, Scala, or Rust.

THE TEAM

You'll join a global engineering organisation working on a platform used by some of the world's largest legal teams. The culture is diverse, inclusive, and driven by high standards. Engineers here work on genuinely complex technical problems at scale — and are supported with the coaching, development, and tooling to keep growing.

COMPENSATION & BENEFITS

Salary

208,000 – 312,000 PLN per year, plus an annual performance bonus and long-term incentives.

Health coverage

Comprehensive health, dental, and vision plans.

Parental leave

Parental leave available for both primary and secondary caregivers.

Flexible working

Flexible work arrangements with a remote-first model.

Company breaks

Two week-long company-wide breaks per year, plus additional time off.

Training investment

Dedicated training investment programme to support ongoing professional development.