Context Engineer - Senior - Consulting - Location OPEN
About the role
We are seeking a Data Engineer with strong semantic data engineering capabilities — someone who can design and build modern data pipelines while also implementing semantic frameworks (ontologies, taxonomies, and knowledge graphs) that enable agentic AI and intelligent data products.
Responsibilities
- Data engineering & platform delivery
- Design, build, and operate scalable data pipelines and integrations that support large-scale data architectures across cloud and hybrid environments.
- Build out new integrations using cloud-native technologies to support continuing increases in data sources, volume, and complexity.
- Extract, transform, and load data from multiple external/internal sources into a single, consistent source to serve business users and data visualization needs.
- Implement processes and systems to drive data reconciliation and monitor data quality.
- Write unit/integration/performance tests and perform analysis required to troubleshoot data-related issues and support resolution.
- Semantic data engineering / context engineering
- Develop and evolve ontologies and semantic models to represent business concepts, relationships, and workflows in support of AI agents and enterprise analytics.
- Build and maintain knowledge graphs that enable contextual reasoning, entity resolution, and semantic integration across domains.
- Define metadata schemas, taxonomies, and contextual rules to support dynamic orchestration, discoverability, and reuse.
- Implement and govern semantic standards and best practices aligned to W3C semantic web standards
- Continuous improvement
- Utilize CI/CD principles to automate deployment of code changes, improving code quality, test coverage, and resilience.
- Evaluate and adopt emerging tools and processes in data engineering and knowledge graph platforms to improve productivity and outcomes.
Qualifications
- A Bachelor's degree in STEM
- 4+ years of relevant experience in software development, data science, data engineering, ETL, and analytics reporting development.
- 3+ years’ experience with native cloud products and services such as AWS, Azure or GCP.
- 2+ years of experience mentoring and leading a team of data engineers, fostering a culture of innovation and professional development.
- Experience designing, building, implementing, and maintaining data and system integrations using dimensional data modelling and development and optimization of ETL pipelines.
- Proven track record of designing and implementing complex data solutions.
- Experience using:
- Data engineering programming languages (e.g., Python)
- Proficiency in OWL, RDF, SPARQL.
- Distributed data technologies (e.g., Pyspark)
- Cloud platform deployment and tools (e.g., Kubernetes)
- Relational SQL databases
- DevOps and continuous integration
- GitHub
- Strong organizational skills with the ability to manage multiple projects simultaneously and operate as a leading member across globally distributed teams to deliver high-quality services and solutions.
- Understanding of database architecture and administration.
- Excellent written and verbal communication skills, including storytelling and interacting effectively with multifunctional teams and other strategic partners.
- Strong problem solving and troubleshooting skills.
- Ability to work in a fast-paced environment and adapt to changing business priorities.
Skills and attributes for success
- Partner with Business Analysts and Solution Architects to translate business requirements into technical specifications aligned to the intended design.
- Collaborate with AI/ML engineers to embed a semantic context layer into agentic workflows and data products.
- Support advanced analytics and AI use cases by improving data readiness, meaning, lineage, and interpretability.
- Collaborate with AI/ML engineers to create data products for analytics and data scientist team members to improve productivity.
- Advise, consult, mentor and coach other data and analytic professionals on data standards and practices, promoting the values of learning and growth.
- Foster a culture of sharing, re-use, design for scale, stability, and operational efficiency of data and analytical solutions.
- Develop solutions for complex problems
- Suggest changes to policies and establish new procedures
- Provide direction and feedback to team members
Pay
The base salary range for this job in all geographic locations in the US is $106,900 to $176,500. The base salary range for New York City Metro Area, Washington State and California (excluding Sacramento) is $128,400 to $200,600. Individual salaries within those ranges are determined through a wide variety of factors including but not limited to education, experience, knowledge, skills and geography.
Schedule
Join us in our team-led and leader-enabled hybrid model. Our expectation is for most people in external, client serving roles to work together in person 40-60% of the time over the course of an engagement, project or year.