The Staff Data Engineer will design, build, and optimize large-scale data capabilities, focusing on automation and intelligent decision-making within the organization. Responsibilities include software design, implementation, and promoting best engineering practices.
Posting Type
Remote
Job Overview
Relativity powers some of the world’s most critical legal, compliance, and investigative work. From corporate compliance to human rights, our platform safeguards global investigations while handling petabytes of sensitive evidence. Our teams build the distributed data foundation that drives AI-assisted analysis across billions of documents every day. We are defining the future of Legal Data Intelligence—technology that helps organizations Organize Data, Discover Truth, and Act on It.As a Staff Data Engineer, you will be a hands-on technical leader responsible for designing, building, and optimizing high-performance data systems operating at massive scale. You’ll work across data orchestration tools, modern processing frameworks, and distributed compute to ensure our platform is resilient, scalable, and ready to power the next generation of AI capabilities.
This role blends deep technical execution with strategic leadership. You’ll shape architectural direction, provide design oversight across teams, and elevate data engineering standards across the organization. Your work will directly influence some of the world’s most sensitive legal processes—from real-time investigations to large-scale litigation.
Job Description and Requirements
What You’ll Do
- Architect, build, and operate distributed data systems that process massive volumes of structured and unstructured data.
- Design and deliver scalable, secure, and observable data integration and ETL pipelines using Databricks, dbt, and modern workflow orchestration tools—ensuring end-to-end data quality and availability.
- Partner with AI/ML engineers and data scientists to develop robust data foundations that accelerate model training, experimentation, and production deployment.
- Drive innovation in data infrastructure, workflow automation, and platform resiliency to expand analytical and AI capabilities.
- Collaborate closely with product, AI/ML, and platform teams to deliver data solutions that support critical business and customer outcomes.
- Provide architectural direction and design guidance across projects, ensuring alignment with platform strategy and engineering best practices.
- Mentor engineers, contribute to engineering standards, and champion a culture of high performance and reliability.
- 8+ years of experience in data engineering, data architecture, or backend systems development at scale.
- Proven ability to design and optimize complex, high-volume data systems and pipelines for performance, scalability, security, and reliability.
- Deep expertise in data modeling, ETL/ELT methodologies, and workflow orchestration.
- A strong record of technical leadership—guiding architecture, leading major data initiatives, and mentoring engineers.
- Excellent communication and collaboration skills, with the ability to articulate complex concepts to technical and non-technical audiences.
- A passion for using data to drive insight and clarity—not just to move pipelines.
- Hands-on experience with modern big-data and streaming technologies (e.g., Spark/Databricks, Kafka) in AWS, Azure, or GCP.
- Expertise in orchestration and transformation tools (e.g., Airflow, dbt) and cloud data warehouses such as Snowflake or BigQuery.
- Background in building data systems that power machine learning or AI-driven applications.
- Experience leading modernization or migration of large-scale data platforms.
- Familiarity with observability, operational excellence, and cost-optimization strategies for distributed data systems.
- First 3 months: Deliver key architectural enhancements and develop deep fluency in our platform, data domains, and stakeholder ecosystem.
- 6 months: Establish ownership over a major data system end-to-end, with broad authority to improve performance, scalability, and data quality.
- 12 months: Lead cross-team initiatives that elevate Relativity’s analytics and AI capabilities; mentor others and raise the bar for data engineering across the organization
- Impact that matters: Your work enables investigations, litigation, and compliance efforts that affect industries—and lives—around the world.
- Modern technology: Build on a cutting-edge data stack and operate at a scale few companies can match.
- Career growth: Opportunities to lead, innovate, and broaden your influence across AI, product, and platform ecosystems.
- Inclusive culture: We value diverse perspectives and foster an environment where everyone can thrive.
- Competitive rewards: Strong compensation, equity, flexible work options, and ongoing professional development.
Relativity is committed to competitive, fair, and equitable compensation practices.
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:
$174,000 and $262,000The 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.
Suggested Skills:
Algorithms, Automation, Debugging, Distributed Systems, Performance Tuning, Problem Solving, Project Management, Software Development, System Designs, Technical LeadershipTop Skills
Spark
C#
Data Lake
Kubernetes
Lakehouse
Python
Rust
Scala
Relativity Chicago, Illinois, USA Office
We’re a community of passionate, life-long learners tackling challenging problems. We care about each other and about our community.
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