Advanced Data Platform Engineer

43 378.72 - 65 068.08 USDGross per year - Permanent
Python

Advanced Data Platform Engineer

Python
Remote, Katowice +4 Locations

TechTree

Full-time
Permanent
Mid
Remote
43 378.72 - 65 068.08 USD
Gross per year - Permanent

Job description

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. Over 75% of our business has transitioned to our cloud platform, and we are 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 infrastructure you build will have real consequence.

ABOUT THE ROLE

We're building a specialised team focused on enabling advanced analytics and reporting capabilities across our internal data ecosystem. As an Advanced Data Platform Engineer, you'll design and implement scalable, cloud-native data platforms that integrate modern lakehouse technologies, distributed compute frameworks, and cloud-native services to support diverse analytical use cases at enterprise scale.

The role emphasises technical depth — performance optimisation, governance best practices, and the kind of engineering rigour that keeps vast datasets accessible, secure, and compliant. You'll work closely with internal teams to deliver curated datasets and self-service analytics capabilities, and you'll participate in on-call rotations as part of shared team responsibility.

WHAT YOU'LL WORK ON

Data pipeline and distributed systems design

Design and implement complex data pipelines and distributed systems using Spark and Python, applying clean code principles, modular design, CI/CD, automated testing, and thorough code reviews.

Lakehouse platform development

Develop and maintain lakehouse capabilities with Delta Lake and Apache Iceberg, ensuring reliability, performance, and long-term maintainability at scale.

Analytics workflow enablement

Integrate dbt for SQL transformations running on Spark. Deliver curated datasets and self-service analytics capabilities that empower internal stakeholders to explore data independently.

Data warehousing optimisation

Optimise Databricks and Snowflake environments for performance and scalability. Drive cost optimisation and performance tuning across Spark jobs and cloud-native infrastructure.

Observability and governance

Implement observability and governance frameworks including data lineage tracking and compliance controls, ensuring data remains secure and auditable.

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 Python and SQL — the foundation for everything you'll build here.

Apache Spark

Solid experience with Spark for distributed data processing at scale, including performance tuning and optimisation.

Lakehouse architecture

Expertise in Delta Lake and/or Apache Iceberg. You understand the tradeoffs and have used these in production environments.

Analytics tooling

Familiarity with dbt, Databricks, and Snowflake for analytics workflows and SQL transformation pipelines.

Software engineering fundamentals

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

Infrastructure and containerisation

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

Scalability and cost optimisation

Understanding of performance tuning, scalability strategies, and cost optimisation for large-scale 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

160,000 – 240,000 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.

Tech stack

    English

    C1

    Python

    nice to have

    SQL

    nice to have

    Apache Spark

    nice to have

    Delta Lake

    nice to have

    Databricks

    nice to have

    Snowflake

    nice to have

Office location

Advanced Data Platform Engineer

43 378.72 - 65 068.08 USDGross per year - Permanent
Summary of the offer

Advanced Data Platform Engineer

Remote, Katowice
TechTree
43 378.72 - 65 068.08 USDGross per year - Permanent
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