Strategic Legal Practices is seeking a self-starting Data Engineer to help shape how a high-impact litigation firm leverages data. In this role, you’ll take ownership of building scalable pipelines and analytics solutions that power decision-making across the organization.

This is a high-growth opportunity for an ambitious engineer who thrives in fast-paced environments and wants to make a direct business impact. Whether you're coming from a high-growth startup or a large organization and looking for more autonomy, this role offers the chance to lead meaningful data projects from day one.

Our ideal candidate is passionate about solving real-world problems with data, communicates clearly, and enjoys building creative, production-ready solutions that drive the business forward.

Responsibilities include, but are not limited to:

• Collaborate with stakeholders to gather requirements and develop secure, timely, accurate, trusted, and extensible data models
• Seek out opportunities where data can drive impact, and proactively work with teams across the organization to make those solutions a reality
• Become a trusted partner to SLP leadership by delivering data solutions that improve operational effectiveness
• Design and build scalable, maintainable data pipelines and analytic solutions across various business domains
• Support self-service analytics by enabling access to clean, modeled data for analysts and business users
• Monitor data quality and availability, implementing processes to ensure reliability of critical datasets
• Diagnose and resolve issues in development, staging, and production environments
• Provide operational support, including issue investigation, incident response, and remediation
• Maintain and extend existing platform management tooling and codebases (e.g., Python, Java, SQL, Ansible, CloudFormation)

Qualifications:

• 3+ years of experience in an analytics-focused role (Analytics Engineer, Data Engineer, or Analyst/Consultant with a strong engineering background)
• Required: Hands-on experience with Palantir Foundry — strong proficiency expected across pipeline building, ontology/data modeling, and operational deployment
• Energized by business impact and a self-starter: you’d rather build an imperfect data model quickly that’s widely used than a perfect model that goes unused
• Thrive in cross-functional projects involving both complex technical requirements and user-focused workflows
• Expert in SQL and comfortable with Python or other programming languages
• Familiarity with modern data stack tools: dbt, Redshift, Looker/Tableau, and other analytics platforms

Preferred Qualifications:

• Demonstrated experience using data engineering practices to support generative AI applications
• Experience designing pipelines that feed high-quality, well-structured data into LLM-powered workflows
• Strong understanding of how to build and serve data models that power automated, AI-driven solutions across business functions
• Familiarity with tools and frameworks used in generative AI pipelines (e.g., vector databases, embedding generation, prompt engineering)
• Ability to work cross-functionally to identify high-impact automation opportunities using generative AI