Join EY and embark on a career journey tailored to you, leveraging our global reach, supportive culture, and advanced technology to help you achieve your best. Your unique perspective is invaluable as we strive to enhance EY and build a better working world.

This role focuses on providing essential data engineering services for projects and programs supporting Information Security technology. As an individual contributor, you'll collaborate with business and technology leaders to develop, build, and refine secure, scalable data platforms, ETL processes, and integrations. These efforts are crucial for strengthening reporting, analytics, governance, and operational decision-making within the cybersecurity domain.

Key responsibilities include collaborating deeply with stakeholders across business units to grasp and document complex data needs, translating them into precise technical specifications. You will create and maintain detailed documentation for data models (conceptual, logical, physical), data dictionaries, and data flow diagrams, supporting critical functions like cybersecurity reporting, risk analytics, compliance monitoring, vulnerability management, identity governance, and security operations.

Utilize agile methodologies for iterative data model design aligned with sprint goals, avoiding premature complexity. Implement robust data lineage and metadata management practices to boost data governance and auditability. Conduct thorough data profiling and quality assessments, supporting the implementation of validation and business rules. Drive modernization, automation, and continuous improvement throughout the data engineering lifecycle and assist leadership in shaping data strategy for optimal alignment with organizational objectives.

A strong command of SQL and T-SQL for database querying, manipulation, and management is essential. Proficiency is required in data storage solutions like SQL, Databricks, Azure Blob Storage, Dataverse, and Microsoft Graph, alongside expertise in designing, documenting, and implementing ETL processes.

You should possess deep knowledge of ER/Dimensional Modeling techniques, including star and snowflake schemas for both data warehouse and OLTP environments. Hands-on experience with industry-standard database modeling tools such as ER/Studio and Visio is expected. A solid understanding of data governance principles, including data quality, metadata management, and data security, is also required.

Experience with AI tools in modeling practices and synthetic data generation is considered a significant advantage. This role demands at least 5 years of experience in the technical skills mentioned above. Strong business acumen is demonstrated through effective partnerships with architects, engineers, product owners, and project teams, alongside the ability to collaborate with senior stakeholders to align requirements, priorities, and delivery outcomes. Excellent consulting, communication, collaboration, and problem-solving skills within a matrixed environment are crucial.