Senior Semantic Data Engineer

At Prologis, we don’t just lead the industry—we define it with a 1.3 billion square foot portfolio and an annual throughput of approximately $3.2 trillion. We create the intelligent infrastructure that powers global commerce, seamlessly connecting the digital and physical worlds. From agile supply chains to energy solutions, our ecosystems help your business move faster, operate smarter and grow sustainably. With unmatched scale, innovation and expertise, Prologis is a category of one—not just shaping the future of logistics but building what comes next.

Job Title: Senior Semantic Data Engineer Company: Prologis A day in the life Prologis is transforming how work gets done by bringing trusted data, automation, and AI into the core of its operations. As a Senior Semantic Data Engineer on the Data Solutions team, you will help create a shared enterprise understanding of business concepts, relationships, rules, and measures so people, applications, processes, and AI can interpret and use data consistently.

This multidisciplinary role combines senior data engineering, business analysis, semantic modeling, AI evaluation, and enablement, with close partnership across business leaders, domain experts, and technical teams. You will carry solutions from discovery through production, helping Prologis improve decision confidence, accelerate solution delivery, and scale automation and AI without recreating business logic for each use case.

Key responsibilities include: Design and deliver trusted, reusable Snowflake data products for business domains, translating source data into certified dimensional structures, reusable views, and data contracts while resolving identity and modeling historical change. Build and maintain the semantic layer by defining shared business concepts, terminology, relationships, rules, and measures that support consistent use of enterprise data across analytics, applications, business processes, automation, and AI.

Implement semantic data products using Snowflake Cortex semantic views and analytical Cortex Agents, applying approved AI capabilities to improve delivery speed, quality, and consistency while remaining accountable for outputs. Validate semantic data products for business accuracy, data quality, usability, performance, security, and production readiness.

Develop and maintain representative business questions, verified queries, expected results, and regression tests; investigate inaccurate or inconsistent AI-generated answers and improve the underlying data, semantic model, instructions, or examples. Capture definitions, mappings, ownership, lineage, and user guidance in version-controlled, machine-readable formats and publish this content to the enterprise data catalog through automated processes.

Lead complex semantic-modeling initiatives from business and source discovery through technical design, implementation, production deployment, and continuous improvement, partnering with business owners and domain experts across business functions, processes, systems, and regional variations. Building blocks for success Required: Five or more years of experience in data engineering, data modeling, analytics engineering, or a related discipline.

Experience designing conceptual, logical, physical, and dimensional data models and translating business concepts into production data products, including grain, relationships, metrics, identity, and historical change. Advanced SQL skills. Experience designing and delivering production data products in Snowflake. Experience with semantic layers, reusable metric definitions, and business metadata that support natural-language data access, enterprise search, copilots, or AI agents.

Experience managing technical assets through source control, code review, automated testing, deployment, and change-management practices. Practical experience using approved AI tools in analysis, engineering, documentation, testing, or problem-solving, with disciplined validation of AI-generated outputs. Communication and facilitation skills demonstrated through work with business stakeholders, translation between business and technical teams, ambiguity resolution, influence without direct authority, and leadership across collaborating teams.

Preferred: Bachelor’s degree in Computer Science, Information Systems, Data Management, Engineering, or a related field, or equivalent practical experience. Experience with Snowflake Cortex semantic views, Cortex Analyst, Cortex Agents, or comparable AI-enabled semantic-layer technologies. Experience creating evaluation datasets, verified query libraries, or validation frameworks for analytics, natural-language-to-SQL, or AI solutions. Experience with enterprise data catalogs, metadata management, lineage, and data-quality platforms.

Experience using Python or a similar programming language and machine-readable formats such as YAML to create and maintain data and metadata assets, including exposure to APIs or MCP-based integrations; exposure to controlled vocabularies, taxonomies, knowledge graphs, or ontologies is also useful. Demonstrates willingness and capability to leverage emerging technology, automation, and AI tools to improve efficiency, quality, and speed. Exercises sound judgment, creative thinking, and accountability for outcomes. Hiring Salary Range of: $104,000 - $144,000.

Salary and whole compensation package (bonus target) to be determined by the candidate’s location, education, experience, knowledge, skills, and abilities, as well as internal equity and alignment with market data. People First Each of us working at Prologis plays an essential role in the enduring success of our company. We value people who are decisive, courageous and adaptable. While we are one company, locations and departments operate with autonomy and accountability. Individuals take the initiative here.

When you join Prologis, you work shoulder to shoulder with some of the top talent in the industry to do the best work of your career. Every employee belongs. Every employee contributes. Employees advance their careers here. As a successful global enterprise, Prologis has never lost sight of what matters most, our strong belief that our people are the most important part of our business. And because of that, we provide a generous total rewards package and take a lot of time to focus on quality management and leadership development. People come first here.

All full-time roles in the US come with a robust benefits package which includes healthcare, dental, and vision insurance for employees and eligible dependents. Prologis also offers several other wellness, financial, and work/lifestyle-specific benefits. Our 401(k) retirement plan has a company match of 50% up to 12% of eligible compensation. We also offer generous PTO with a starting accrual of 22 days a year in addition to paid holidays and volunteer time. All job offers are contingent upon successful completion of background verification.

Prologis is an Equal Opportunity/Affirmative Action employer and all qualified applicants will receive consideration for employment without regard to race, color, religions, sex, national origin, sexual orientation, gender identity, disability status, protected veteran status, or any other characteristic protected by law.

Employment Type: Full time Location: San Francisco, California Additional Locations: Atlanta, Georgia, Chicago, Illinois, Columbus, Ohio, Dallas, Texas, Denver, Colorado, Nashville, Tennessee, New York, New York, Phoenix, Arizona, Seattle, Washington We are builders, thinkers and doers—creating more than space, we power global commerce. We seek and attract top talent from around the world and foster a culture where diverse ideas fuel innovation, collaboration and excellence

• Minimum five years’ experience in data engineering, modeling, or analytics with advanced SQL and Snowflake production data product delivery.
• Proven skills in designing semantic layers, reusable metrics, business metadata, and managing technical assets via source control and automated testing.
• Strong communication and facilitation abilities working with business and technical teams, plus practical experience using AI tools with disciplined output validation.