Senior Distributed Data Platform Engineer
Relativity is building a specialized team focused on enabling advanced analytics and reporting capabilities across our internal data ecosystem. This team will design and maintain data platforms that integrate modern lakehouse technologies, distributed computing frameworks, and cloud‑native services to support diverse analytical use cases and enterprise‑scale insights.
Posting Type
Remote
Responsibilities
- Design and implement scalable data pipelines and distributed systems using Spark and Python to process and transform large‑scale datasets for analytics and reporting.
- Apply software engineering best practices, including clean code, modular design, CI / CD, automated testing, and code reviews.
- Develop and maintain lakehouse capabilities with Delta Lake and Iceberg, ensuring data reliability, versioning, and performance optimization.
- Enable analytics workflows by integrating dbt for SQL transformations running on Spark.
- Collaborate with internal teams to provide curated datasets and self‑service capabilities for reporting and advanced analytics.
- Integrate and optimize data‑warehousing solutions such as Databricks and Snowflake for scalable storage and query performance.
- Build platforms that allow secure and compliant access to diverse data sources for analytical use cases.
- Implement observability and governance frameworks, including data lineage, quality checks, and compliance controls.
- Drive performance tuning and cost optimization across Spark jobs and cloud‑native environments.
- Champion best practices in CI / CD, automated testing, and infrastructure‑as‑code for data engineering workflows.
Core Requirements
Strong programming skills in Python and SQL.Solid understanding of software engineering principles, CI / CD, and automated testing.Hands‑on experience with Apache Spark for distributed data processing.Expertise in Delta Lake and / or Apache Iceberg for lakehouse architecture.Experience with dbt for data modeling and transformation workflows.Familiarity with Databricks and Snowflake for data warehousing and analytics.Understanding of data governance, lineage, and compliance in multi‑tenant environments.Familiarity with Kubernetes, Docker, and infrastructure‑as‑code tools.Understanding of performance tuning, scalability strategies, and cost optimization for large‑scale systems.Nice to Have
Exposure to event‑driven architectures and advanced analytics platforms.Experience enabling self‑service analytics for internal stakeholders.Experience in any of the following languages : Java, Scala, Rust.Benefits
Comprehensive health, dental, and vision plans.Parental leave for primary and secondary caregivers.Flexible work arrangements.Two week‑long company breaks per year.Unlimited time off.Long‑term incentive program.Training investment program.Compensation
This position is eligible for total compensation which includes a competitive base salary, an annual performance bonus, and long‑term incentives.
The expected salary range for this role is between 181,000 and 271,000 PLN.
EEO Statement
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin, disability or protected veteran status, or any other legally protected basis, in accordance with applicable law.
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