ESP Security Data Engineer

• Collaborate extensively with stakeholders across various business units to me-ticulously understand and document intricate data requirements, translating them into actionable technical specifications
• Create and maintain comprehensive documentation of conceptual, logical and
  physical data models, data dictionaries, and data flow diagrams that enable cyberse-
• curity reporting, risk analytics, compliance monitoring, vulnerability management, iden- tity governance, and security operations.
• Utilize an agile methodology to incrementally design data models according to sprint requirements, avoiding premature over-engineering
• Implement data lineage and metadata management practices, enhancing data governance and audibility
• Lead data profiling and data quality assessments and support the implementation of data validation and business rules
• Drive modernization, automation and continuous improvement across the data engineering lifecycle
• Assist leadership with defining data strategy and ensuring alignment with organizational objectives

Experience Technical Skills

• SQL and T-SQL: Mastery of SQL and T-SQL for querying, manipulating, and managing relational databases
• Data storage: SQL, Databricks, Azure Blob Storage, Dataverse and Microsoft Graph
• ETL Processes: Proficiency in designing, documenting and implementing ETL (Extract, Transform, Load)
• ER/Dimensional Modeling: Expertise in utilizing Entity-Relationship (ER) diagrams and dimensional modeling techniques, including star and snowflake schemas for both data warehouse and OLTP environments
• Database Tools: Hands-on experience with industry-standard database
• modeling tools like ER/Studio, and Visio Data Governance: Understanding of data governance principles and practices,including data quality, metadata management, and data security.
• AI: Experience with using AI tools in modeling practices and synthetic generation is a plus Information Security:
  • 5+ years of experience in the technical skills listed above