Context Engineer - Manager - Consulting - Location OPEN

About the role

EY seeks a Data Engineer with strong semantic data engineering capabilities to join our team. This role involves designing and building modern data pipelines while implementing semantic frameworks 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.
• 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
• 6+ 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.
• Demonstrated understanding and experience using: Data engineering programming languages (e.g., Python), 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

• Strong ability to manage change, lead teams effectively, and maintain excellent relationship management skills.
• Adept at problem-solving, critical thinking, and have a deep expertise in data architecture and software engineering.
• 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 $125,500 to $230,200. The base salary range for New York City Metro Area, Washington State and California (excluding Sacramento) is $150,700 to $261,600. 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

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.