Context Engineer - Manager - Consulting - Location OPEN

About the role

EY delivers unparalleled tech consulting services in data strategy, business intelligence, digital, machine learning and Artificial Intelligence. We support and enable big ideas, always with the ambitions to keep doing more.

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.

Requirements

• 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.
• Experience with 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

Qualifications

• 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

Skills and attributes for success

• Strong business acumen with the ability to manage complex client relationships
• Proven experience in managing and leading teams within a dynamic environment
• Excellent communication and interpersonal skills
• Experience with agentic AI systems or AI orchestration frameworks.
• Knowledge of data fabric, data mesh, or AI4Data architectures.
• Background in enterprise data management (MDM, metadata, governance).
• Experience with cloud data platforms like Snowflake and Databricks.
• Experience in leading and influencing teams, with a focus on mentorship and professional development.
• A passion for innovation and the strategic application of emerging technologies to solve real-world challenges.
• The ability to foster an inclusive environment that values diverse perspectives and empowers 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

We offer a flexible vacation policy where you'll decide how much vacation time you need based on your own personal circumstances. You'll also be granted time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well-being.