Data & Analytics (ML-Enabled Systems)

Thomson Reuters•Frisco, TX

20h•Hybrid

About The Position

This posting is for proactive recruitment purposes and may be used to fill current openings or future vacancies within our organization. Data & Analytics (ML-Enabled Systems) We experiment, we build, we deliver. We support the organization and our product teams through foundational research and development of new products and technologies. Thomson Reuters Labs innovates collaboratively across our core segments in Legal, Tax & Accounting, Government, and Reuters News. We undertake a diverse portfolio of projects while investing in long-term research for the future. About the Role: Are you passionate about building data infrastructure that powers cutting-edge AI evaluation systems? Thomson Reuters Labs is seeking a Data Engineer to join our AI data, evaluation, and governance team and help shape how we measure, monitor, and improve AI-powered legal products. In this role as a Data Engineer, you will: Build & Deploy Product Analytics Infrastructure: Design and implement scalable data pipelines and analytics systems that transform customer feedback and product traces into actionable insights across AI-powered legal products. Enable AI Evaluation at Scale: Build data workflows to enable the deployment of automated evaluation metrics as production analytics to continuously track product quality, detect errors, and alert teams to regressions before they impact customers. Establish Data Governance & Quality Standards: Develop technical governance infrastructure for manual and automated review of AI product data, particularly for small and medium law firms, ensuring data quality, security, and compliance. Drive Metric Development: Analyze product traces and customer feedback to identify quality issues and patterns that inform the development of new evaluation metrics and feed into product roadmap decisions. Support Cross-Functional Teams: Partner closely with Product Scientists, Research Engineers, and Subject Matter Experts to implement configurations, build reporting dashboards, and create self-service tools for metric implementation. Advance AI Evaluation Best Practices: Contribute to the development and scaling of automated evaluation capabilities and establish best practices for AI evaluation and analytics across Thomson Reuters pillars (Legal, Tax & Accounting, and Reuters News).

Requirements

Bachelor's or Master's degree in Computer Science, Data Engineering, Software Engineering, or related technical field
8+ years of professional experience in data engineering, analytics engineering, or related roles
Strong programming skills in Python and SQL with experience building production data pipelines
Hands-on experience with modern data stack technologies (e.g., Snowflake, AWS, PowerBI, or similar orchestration, transformation, or analytics tools)
Experience with cloud platforms (e.g., AWS, or similar) and their data services
Proven ability to design and implement scalable ETL/ELT pipelines for structured and unstructured data
Experience with data warehousing, data modeling, and analytics infrastructure
Strong understanding of data governance, data quality, and security best practices
Excellent communication skills to collaborate with cross-functional teams including scientists, engineers, product managers, and subject matter experts
Self-driven attitude with ability to manage projects independently and meet deadlines
Snowflake, Power BI, SQL, Python ETL/ELT pipelines, data lakes, AWS/cloud
Experience with customer data, user behavior, and product analytics
Ability to build dashboards, define KPIs, and deliver insights
Experience working with AI/ML data (prompts, model outputs, evaluation datasets)
Ability to analyze and monitor AI performance
Experience with data quality, governance, and handling sensitive data (PII)
Build automated, scalable data pipelines and workflows

Nice To Haves

Familiarity with LLMs is a plus (not required)
Experience with AI/ML systems, particularly in evaluation, monitoring, or observability
Familiarity with LLM applications and challenges in measuring generative AI quality
Experience building analytics for customer-facing products or SaaS applications
Knowledge of data visualization tools (e.g., PowerBI, Streamlit, Snowflake)
Experience working with product analytics or user behavior data
Background in building self-service analytics or internal tooling
Understanding of legal, compliance, or regulated industry data requirements
Experience with real-time data processing and alerting systems

Responsibilities

Design and implement scalable data pipelines and analytics systems that transform customer feedback and product traces into actionable insights across AI-powered legal products.
Build data workflows to enable the deployment of automated evaluation metrics as production analytics to continuously track product quality, detect errors, and alert teams to regressions before they impact customers.
Develop technical governance infrastructure for manual and automated review of AI product data, particularly for small and medium law firms, ensuring data quality, security, and compliance.
Analyze product traces and customer feedback to identify quality issues and patterns that inform the development of new evaluation metrics and feed into product roadmap decisions.
Partner closely with Product Scientists, Research Engineers, and Subject Matter Experts to implement configurations, build reporting dashboards, and create self-service tools for metric implementation.
Contribute to the development and scaling of automated evaluation capabilities and establish best practices for AI evaluation and analytics across Thomson Reuters pillars (Legal, Tax & Accounting, and Reuters News).

Benefits

flexible vacation
two company-wide Mental Health Days off
access to the Headspace app
retirement savings
tuition reimbursement
employee incentive programs
resources for mental, physical, and financial wellbeing
market competitive health, dental, vision, disability, and life insurance programs
competitive 401k plan with company match
competitive vacation, sick and safe paid time off
paid holidays
parental leave
sabbatical leave
optional hospital, accident and sickness insurance paid 100% by the employee
optional life and AD&D insurance paid 100% by the employee
Flexible Spending and Health Savings Accounts
fitness reimbursement
access to Employee Assistance Program
Group Legal Identity Theft Protection benefit paid 100% by employee
access to 529 Plan
commuter benefits
Adoption & Surrogacy Assistance
Tuition Reimbursement
access to Employee Stock Purchase Plan