Act as a thought leader, constantly evaluating emerging trends in knowledge graphs, semantic AI, prompt engineering, and related technologies to strategically enhance DPR’s capabilities in knowledge representation and data understanding.
Participate in all phases of the project lifecycle and lead data architecture initiatives.
Develop standards, guidelines, and best practices for knowledge representation, semantic modeling, and data standardization across DPR to ensure a clear and consistent approach within the enterprise semantic layer.
Partner closely with analytics engineers and data architects to deeply understand the underlying data models in Snowflake and develop a profound understanding of our business domains and data entities. Provide strategic guidance on how structured data can be seamlessly transformed, optimized, and semantically enriched for advanced AI consumption and traditional BI/Analytics tools.
Lead the effort to establish and maintain comprehensive documentation for all aspects of the semantic layer, which includes defining and standardizing key business metrics, documenting ontological definitions, relationships, usage guidelines, and metadata for all semantic models, ensuring clarity, consistency, and ease of understanding for all data users.
Rapidly prototype high-priority solutions in cloud platforms, demonstrating their feasibility and business value.
Establish and refine operational processes for semantic model development, including intake mechanisms for new requirements (e.g., from AI prompt engineering initiatives) and backlog management, ensuring efficient and iterative delivery.
Integrate the semantic layer to serve as an AI-ready knowledge base, enabling applications such as advanced analytics, prompt engineering for large language models, and intelligent data discovery while ensuring seamless connectivity and holistic data understanding across the enterprise.
Evaluate and monitor the performance, quality, and usability of semantic systems, ensuring they meet organizational objectives, external standards, and the demands of AI applications.
Requirements
sql
python
snowflake
pyspark
devops
semantic modeling
3+ years of experience with data warehousing concepts, dimensional modeling, and data governance principles as they relate to structuring data for semantic enrichment.
Skilled in orchestrating and automating data pipelines within a DevOps framework.
Proficiency in SQL and experience working with cloud-based data warehouses, preferably Snowflake.
Strong analytical and problem-solving skills with keen attention to detail and the ability to translate complex business concepts into logical ontologies and knowledge graph structures.
Strong proficiency in SQL, Python, and PySpark.
3+ years of experience developing data solutions specifically for AI/ML applications leveraging structured data.
Proven expertise in data analysis, data modeling, and data engineering with a focus on cloud- native data platforms.
Familiarity with agile methodologies, and experience working closely with cross functional teams to manage technical backlogs.
5+ years of hands-on experience in semantic modeling, ontology engineering, knowledge graphs, or related AI data preparation.
Benefits
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Training + Development
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Interview process
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Visa Sponsorship
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Security clearance
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Company
Overview
Founded in 1990
Year Established
The company has been in operation since 1990, contributing to its extensive experience and reputation.
A forward-thinking construction company that has grown from a small operation to a nationwide leader in the industry.
Focuses on complex, large-scale projects and is known for its expertise in delivering innovative, high-quality construction solutions.
Successfully completed projects across a range of sectors, including commercial, healthcare, education, and data centers, standing out for its ability to manage large budgets and tight schedules.
Notably completed several landmark projects, including high-tech facilities and cutting-edge educational buildings, often involving collaboration with some of the largest tech and medical organizations in the world.
Strong track record in renewable energy, particularly in solar and energy-efficient construction, positioning them as a leader in sustainable building practices.
Approach to construction is driven by technology and innovation, consistently pushing boundaries to ensure maximum efficiency and quality in its operations.
Commitment to performance and safety has earned a reputation for delivering projects that meet and exceed client expectations.
From healthcare campuses to advanced research labs, the company’s dedication to excellence ensures each project is tailored to the unique needs of the client and the community.
Culture + Values
We strive to be the most trusted builder in the world.
We are passionate about building great things.
We collaborate to innovate and continuously improve.
We take ownership and are accountable to our people and partners.
We respect and support one another.
We build long-lasting relationships with clients, partners, and employees.
Environment + Sustainability
Net-Zero by 2030
Carbon Emissions Target
Aiming to achieve net-zero carbon emissions by 2030.
Committed to reducing environmental impact through sustainable building practices and operations.
Implementing waste diversion strategies to promote zero waste in all projects.
Using energy-efficient solutions in construction to minimize carbon footprints and energy use.
Focusing on reducing water usage and promoting water conservation in projects.
Promoting the use of sustainable materials in construction projects to reduce environmental impact.
Inclusion & Diversity
The company has a clear focus on increasing gender diversity within the workforce.
The company has set a goal of increasing the representation of women in leadership roles.
The company aims to create an inclusive environment where employees from diverse backgrounds feel valued and supported.
The company tracks its gender-related statistics and is working toward enhancing gender equity in its workforce.