• Design, build, and maintain scalable, robust, and automatable data pipelines to support ingestion and processing across structured, unstructured, and media data types (including audio, text, and video). • Partner with product, data science, and business stakeholders to translate business goals and customer needs into engineering requirements — starting with the desired outcome and working backwards into concrete, scalable solutions. • Improve data quality, observability, lineage, and reliability across our modular processing pipeline architecture. • Build and maintain core data infrastructure components (e.g., ingestion APIs, metadata services, observability tooling) that support parallel processing, microservices, and config-driven workflows. • Help evolve our approach to handling time-series and media content at scale, optimizing for throughput, cost efficiency, and real-world performance. • Collaborate across teams to validate production data flows, support onboarding of new datasets, and troubleshoot issues quickly and effectively.

• Design, build, and maintain scalable, production-grade ETL pipelines • Own and continuously improve data quality frameworks, validation rules, and monitoring • Ensure reliability of data pipelines (handling failures, inconsistencies, late data) • Deliver clear, actionable insights for both technical and non-technical stakeholders • Build and maintain dashboards, reporting systems, and alerting mechanisms • Investigate and resolve data issues with a focus on root cause and long-term stability • Evaluate and improve the data architecture and technology stack • Contribute to code quality, standards, and best practices within the team • Support DevOps-related processes where needed • Align technical solutions with product goals and customer needs

Job Title: Data Engineer – MVA Inference & Audience Development (Remote) Company: Liberty Legal Network Location: Remote (Global) Job Type: Full-Time About Liberty Legal Network Liberty Legal Network is a legal technology platform that uses AI-powered matching to connect individuals with specialized law firms nationwide. Our mission is to simplify access to legal representation while improving outcomes through intelligent data, precision matching, and scalable technology. About the Role We’re looking for a Data Engineer to design and build scalable, privacy-first data systems that power audience development and marketing intelligence. In this role, you’ll develop reliable data pipelines and inference systems using aggregated, historical data—ensuring all infrastructure meets strict compliance and governance standards. You’ll collaborate closely with Growth and Compliance teams to deliver high-quality, actionable insights. What You’ll Do - Design, build, and maintain ETL/ELT data pipelines - Develop reusable inference layers for audience modeling - Create standardized, audit-ready segmentation workflows - Implement data governance practices (lineage, validation, logging) - Perform geospatial aggregation (ZIP, county, corridor-level data) - Partner with Growth and Compliance teams to support data-driven initiatives What Success Looks Like (First 60–90 Days) - Production-ready, monitored data pipelines - Established and governed inference layer library - Consistent, scalable segmentation workflows - Measurable improvements in audience targeting performance What You Bring - Strong SQL skills and experience with data modeling - Proficiency in Python - Experience with cloud platforms (AWS, GCP, or Azure) - Familiarity with modern data warehouses (Snowflake, BigQuery, Redshift) - Experience implementing data governance and quality controls - Experience working with aggregated or geospatial datasets Compliance & Data Standards - Work exclusively with aggregated, historical datasets (45+ days old) - No use of real-time or individual-level data - Apply best practices in data privacy, governance, and auditability - Understand the distinction between inferred insights and direct knowledge - Support vendor compliance and data audit processes Nice to Have - Experience with marketing or audience segmentation systems - Familiarity with privacy frameworks (CCPA, GDPR, TCPA) - Experience with tools such as dbt, Airflow, Dagster, or Spark Compensation Compensation is competitive and based on experience, skills, and location. Why Join Us - Work on impactful technology that improves access to legal services - Build privacy-first data systems in a rapidly evolving space - Collaborate with cross-functional teams in a fully remote environment - Opportunity to shape scalable data infrastructure from the ground up We are committed to equal opportunity and diversity in the workplace. We consider all qualified applicants without regard to race, color, religion, gender, sexual orientation, national origin, disability, or veteran status. All inquiries and applications are kept confidential.

• Build and maintain data pipelines and infrastructure that power data-driven decisions across the firm. • Work within the Data Science team, collaborating with analysts, scientists, and stakeholders to ensure high-quality, accessible data. • Design, build, and optimize ETL pipelines using Microsoft Fabric and Medallion Architecture. • Identify and integrate new data sources; assemble complex datasets aligned to business needs. • Improve infrastructure scalability, data delivery, and process automation. • Monitor data quality, troubleshoot issues, and enforce governance and security standards. • Support business intelligence tools and data models; collaborate with Executive Leadership, App Dev, Marketing, and Finance. • Maintain documentation; participate in monthly on-call rotation.