Lead Distributed Data Platform Engineer
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 platform you lead will underpin how the entire organisation accesses and acts on its data.
ABOUT THE ROLE
We're building a specialised team focused on enabling advanced analytics and reporting capabilities across our internal data ecosystem. As Lead Distributed Data Platform Engineer, you'll combine deep technical expertise with hands-on team leadership — guiding a team in designing and maintaining data platforms that integrate modern lakehouse technologies, distributed compute frameworks, and cloud-native services at enterprise scale.
You'll lead architectural decisions, mentor engineers, and ensure delivery of secure, reliable, and scalable solutions. The role emphasises technical leadership, governance best practices, and a culture of innovation and continuous improvement. You'll also participate in on-call rotations as part of shared team responsibility for platform reliability.
WHAT YOU'LL WORK ON
Team leadership and mentorship
Lead and mentor a team of data platform engineers, promoting collaboration, knowledge sharing, and professional growth. Set and maintain high engineering standards across the team.
Distributed systems architecture
Drive architectural decisions for distributed systems and lakehouse platforms using Spark, Delta Lake, and Iceberg. Facilitate architecture reviews and contribute to design decisions for fault-tolerant, future-ready systems.
Data pipeline and platform delivery
Oversee design and implementation of scalable data pipelines and analytics workflows, ensuring they are reliable, performant, and maintainable at scale.
Engineering best practices
Ensure adherence to clean code, modular design, CI/CD, automated testing, and code review standards across all platform engineering work.
Performance and cost optimisation
Manage performance tuning, scalability strategies, and cost optimisation across cloud-native environments and large-scale distributed workloads.
Governance and observability
Champion governance, observability, and compliance frameworks across all data platforms — ensuring data remains accessible, secure, and auditable.
Stakeholder communication
Communicate effectively with leadership and cross-functional teams to provide updates, resolve blockers, and ensure delivery aligns with business objectives and analytics needs.
WHAT WE LOOK FOR
Proven technical team leadership
Demonstrated experience leading data engineering or platform development teams — mentoring engineers, owning architectural decisions, and driving delivery outcomes.
Python and SQL
Strong programming skills in both Python and SQL applied to production data platform work at scale.
Apache Spark
Hands-on experience with Spark for distributed data processing, including performance tuning and optimisation in production environments.
Lakehouse architecture
Expertise in Delta Lake and/or Apache Iceberg. You understand the trade-offs and have applied these technologies in production at scale.
Analytics tooling
Familiarity with dbt, Databricks, and Snowflake for analytics workflows and large-scale data processing.
Software engineering fundamentals
Solid understanding of software engineering principles — CI/CD, automated testing, clean code, and modular design applied to data platform systems.
Infrastructure and containerisation
Familiarity with Kubernetes, Docker, and infrastructure-as-code tools in cloud-native environments.
Communication and stakeholder management
Strong communication skills with the confidence to operate across engineering teams, cross-functional partners, and senior leadership.
Bonus
Exposure to event-driven architectures and advanced analytics platforms. Experience enabling self-service analytics for internal stakeholders. Experience in Java, Scala, or Rust. Exposure to service mesh and advanced orchestration patterns.
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
270,000 – 406,000 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.
Lead Distributed Data Platform Engineer
Lead Distributed Data Platform Engineer