Data Engineering Manager

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OtherData Engineering Manager

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Quick Summary

Overview

Posting Type Remote Job OverviewWe are expanding our data engineering capabilities to support advanced analytics, scalable data processing, and modern lakehouse architecture.

Requirements Summary

Experience with distributed data processing frameworks (e.g., Spark, Flink) Experience building self‑service analytics or internal data platforms. Understanding of AI/ML workflows and data requirements for model development.

Technical Tools

pythonsnowflakesqlci-cddistributed-systemsetlperformance-managementproject-managementstakeholder-management

Posting Type

Remote

Job Overview

We are expanding our data engineering capabilities to support advanced analytics, scalable data processing, and modern lakehouse architecture. As a Hands On Data Engineering Manager, you will lead and grow a high performing team while contributing directly to the design, implementation, and evolution of core data platforms and pipelines. You will help shape technical direction, support strong engineering practices, and ensure our systems are reliable, efficient, and ready to scale.

Relativity’s scale and breadth provide significant opportunities for rich data exploration and insights. Our data infrastructure ensures that vast datasets remain accessible, secure, and compliant, while enabling innovation across the organization. We are making substantial investments in data lake technology and distributed systems to support future growth and advanced analytics.

Job Description and Requirements

Build, mentor, and develop a strong data engineering team, supporting their growth and fostering a collaborative, learning‑oriented environment.
Encourage a culture focused on continuous improvement and technical excellence.
Support the team in defining and evolving engineering standards that promote high‑quality, reliable, and maintainable software.
Contribute hands-on to data pipelines, platform engineering, and architectural discussions.
Ensure systems are scalable, efficient, observable, secure, and aligned with governance and compliance expectations.
Collaborate with Product, Analytics, and Applied Science teams to shape roadmaps and deliver impactful capabilities.
Communicate clearly with stakeholders, providing transparency on priorities, risks, and progress.

Requirements

~1 min read

2+ years leading data engineering or software engineering teams.
Hands‑on experience building and operating large‑scale data processing systems.
Competence with Python, SQL.
Knowledge of lakehouse technologies such as Delta Lake or Apache Iceberg
Familiarity with modern data platforms such as Databricks or Snowflake.
Solid understanding of software engineering best practices and CI/CD automation.
Strong communication, collaboration, and decision‑making skills.

Nice to Have

~1 min read

Experience with distributed data processing frameworks (e.g., Spark, Flink)
Experience building self‑service analytics or internal data platforms.
Understanding of AI/ML workflows and data requirements for model development.

What We Offer

~1 min read

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 following values:

288 000 and 432 000PLN

The final offered salary will be based on several factors, including but not limited to the candidate's depth of experience, skill set, qualifications, and internal pay equity. Hiring at the top end of the range would not be typical, to allow for future meaningful salary growth in this position.

Budget Management, Engineering Management, Innovation, Leadership, Performance Management (PM), Process Improvements, Project Management, Quality Assurance (QA), Risk Management, Stakeholder Management