Lead Data & AI Engineer Semantic Intelligence

We are looking for a Lead Data & AI Engineer - Semantic Intelligence to build trusted data and semantic foundations that turn enterprise AI into scalable business capability. You will combine data engineering data-product thinking dimensional and semantic modelling application development AI engineering and practical data science. You will own delivery from raw data to AI-enabled decisions. This covers medallion architecture reusable data products semantic models agents and applications.

You will partner early with business product Data & Analytics and technology stakeholders to define outcomes success measures and data needs. You will turn ambiguous challenges into technical designs prototypes and production solutions and you will stay involved through adoption and improvement. This is a hands-on technical leadership role with mentoring responsibilities. It has no direct people management.

• Deliver production-ready Data & AI solutions staying hands-on in investigation architecture coding modelling testing and implementation.
• Build AI-ready data foundations and agentic solutions grounded in structured data governed measures semantic metadata and enterprise knowledge.
• Build production-ready Agentic AI LLM RAG and tool/API orchestration patterns using enterprise engineering standards.
• Build analytical and AI-enabled applications using Fabric application capabilities Rayfin or comparable frameworks integrated with semantic models APIs agents and enterprise security.
• Build robust ELT/ETL pipelines using Snowflake Microsoft Fabric SQL Python dbt Apache Airflow or comparable technologies.
• Implement bronze silver and gold medallion layers with lineage and auditability. Integrate lakehouse warehouse and semantic assets using batch streaming Direct Lake or API patterns.
• Deliver reusable domain-aligned data products with clear ownership data contracts quality controls documentation and consumption interfaces.
• Design dimensional models with explicit grain conformed dimensions facts hierarchies slowly changing dimensions and bridge and relationship patterns.
• Build and optimize Fabric and Power BI semantic models with governed measures DAX relationships and metadata so analytics applications and AI share consistent business context.
• Explore data frame hypotheses engineer features and apply segmentation forecasting classification or anomaly detection where they support a business decision.
• Evaluate analytical and machine-learning approaches against suitable baselines using statistical reasoning validation and business-relevant measures. Explain limitations and integrate useful results into data products or applications.
• Lead end-to-end technical delivery: define scope estimate and plan work manage dependencies and risks coordinate stakeholders and own release readiness adoption and operational handover.
• Mentor engineers through architecture design and code reviews debugging testing and production-readiness practices.
• Build data quality observability automated testing lineage security privacy responsible AI version control and CI/CD into every stage of delivery.
• Turn successful solutions into reusable data products semantic assets agent capabilities and engineering accelerators.
• Start with the business decision or workflow and co-shape outcomes success measures data needs and adoption with stakeholders.
• Move from discovery to prototype to production validating assumptions with real enterprise data and early feedback.
• Measure success by business value trusted metrics adoption engineering quality and reuse. Solve immediate needs while strengthening reusable enterprise foundations.

• 8 years of experience in data engineering analytics engineering AI engineering or closely related technical roles.
• Hands-on experience with Agentic AI LLMs agents RAG and tool/API integration or orchestration.
• Experience building data-driven or AI-enabled applications using Fabric Rayfin or comparable frameworks.
• Experience with Snowflake Microsoft Fabric or comparable analytical platforms including lakehouse and warehouse patterns.
• Strong SQL and Python skills with experience delivering production-grade data solutions.
• Experience delivering data products through bronze silver and gold layers with quality controls lineage and clear consumption interfaces.
• Strong dimensional modelling skills including grain facts dimensions star and snowflake schemas slowly changing dimensions and many-to-many patterns.
• Proven enterprise semantic modelling experience including governed business definitions and reusable measures. Proficiency in Power BI DAX and performance optimization or equivalent technologies.
• Working knowledge of exploratory analysis statistical reasoning feature engineering and practical predictive methods such as forecasting classification or anomaly detection.
• Ability to frame hypotheses select baselines and evaluation measures validate results communicate uncertainty and work with data scientists on modelling approaches.
• Experience with orchestration automated testing version control CI/CD data quality and operational support.
• Ability to lead technical workstreams as a hands-on senior individual contributor and mentor engineers through design and code reviews.
• Experience managing scope estimates dependencies risks releases and operational handover taking solutions from concept through adoption.
• Clear communication with technical business and senior stakeholder audiences.

• Experience with dbt Apache Airflow Git/GitHub and automated deployment frameworks.
• Broader Power BI and Fabric experience across OneLake Lakehouse Warehouse Notebooks Direct Lake and application capabilities.
• Experience with AI solutions grounded in semantic models metadata knowledge graphs or governed enterprise data.
• Experience with agentic frameworks model evaluation observability and responsible AI practices.
• Exposure to machine-learning experimentation feature pipelines and operationalizing lightweight predictive solutions.
• Knowledge of governance privacy security lineage and enterprise architecture.
• Experience delivering reusable data products and platforms in Agile or iterative models.
• Experience designing data contracts and consumption interfaces that enable reuse across analytics applications and AI solutions.
• Experience integrating lakehouse warehouse and semantic assets through batch streaming Direct Lake or API-based patterns with end-to-end lineage and auditability.
• Experience optimizing dimensional and semantic models with conformed dimensions hierarchies bridge tables and complex relationships.
• Experience evaluating analytical and AI-enabled solutions against suitable baselines and business-relevant measures communicating limitations and incorporating stakeholder feedback.
• Experience partnering with business and product stakeholders to take ambiguous needs from discovery and prototyping through production adoption and operational handover.
• Experience creating reusable engineering accelerators and guiding engineers through architecture reviews debugging and production-readiness practices.

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Whats in it For You

• Hybrid Work Model: Weve adopted a flexible hybrid working environment for our office-based roles while delivering a seamless experience that is digitally and physically connected.
• Flexibility & Work-Life Balance: Flex My Way is a set of supportive workplace policies designed to help manage personal and professional responsibilities whether caring for family giving back to the community or finding time to refresh and reset. This builds upon our flexible work arrangements including work from anywhere for up to 8 weeks per year empowering employees to achieve a better work-life balance.
• Career Development and Growth: By fostering a culture of continuous learning and skill development we prepare our talent to tackle tomorrows challenges and deliver real-world solutions. Our Grow My Way programming and skills-first approach ensures you have the tools and knowledge to grow lead and thrive in an AI-enabled future.
• Industry Competitive Benefits: We offer comprehensive benefit plans to include flexible vacation two company-wide Mental Health Days off access to the Headspace app retirement savings tuition reimbursement employee incentive programs and resources for mental physical and financial wellbeing.
• Culture: Globally recognized award-winning reputation for inclusion and belonging flexibility work-life balance and more. We live by our values: Obsess over our Customers Compete to Win Challenge (Y)our Thinking Act Fast / Learn Fast and Stronger Together.
• Social Impact: Make an impact in your community with our Social Impact Institute. We offer employees two paid volunteer days off annually and opportunities to get involved with pro-bono consulting projects and Environmental Social and Governance (ESG) initiatives.
• Making a Real-World Impact:We are one of the few companies globally that helps its customers pursue justice truth and transparency. Together with the professionals and institutions we serve we help uphold the rule of law turn the wheels of commerce catch bad actors report the facts and provide trusted unbiased information to people all over the world.

About Us

Thomson Reuters informs the way forward by bringing together the trusted content and technology that people and organizations need to make the right decisions. We serve professionals across legal tax accounting compliance government and media. Our products combine highly specialized software and insights to empower professionals with the data intelligence and solutions needed to make informed decisions and to help institutions in their pursuit of justice truth and transparency. Reuters part of Thomson Reuters is a world leading provider of trusted journalism and news.

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