Principal Data Engineer

• Provides senior technical expertise with a focus on bank and industry-wide solutions that address capability gaps to create significant value for customers.
• Implements solutions, ensuring efficiency, reliability, scalability, and security; includes planning, evaluating, recommending, designing, operationalizing, and supporting solutions in an industry-leading manner.
• Provides deep technical leadership, sets direction in developing and implementing solutions to address Platform and Journey's emerging business needs and strategies, as well as efficiency opportunities from a technical perspective.
• Advances the overall design, architecture, and technology capabilities in accordance with industry developments.
• Leading authority on data engineering concepts, principals, practices and standards.
• Thought leader on IT risk-based approaches to data engineering and on other domains in technology control/information security fields.
• Sets the direction and oversees the work of other Data Engineering professionals on complex, highly-visible projects of significant profile, strategic importance, and enterprise impact to the bank.
• Establishes and leads Data engineering working groups to achieve goals that impact multiple Journeys and Platforms.
• Provides consultative and strategic guidance to executive leadership.
• Engineering specialist assigned to work autonomously on high profile, complex and high-risk technology initiatives with significant impact to the organization.
• Has a blend of skills in data engineering, data management, architecture, solutions architecture, application security and coding.
• Primarily works at the enterprise level.
• Typically reports to the data engineering practice owner.

• University or Graduate/post graduate degree in Data Management or related Computer Science or Engineering discipline; or equivalent practical experience
• 15+ years of relevant experience in field of specialization
• Advanced proficiency in cloud data platforms (Azure preferred: ADF, Databricks)
• Strong experience with data architecture patterns (batch, streaming, real-time)
• Expertise in data modeling (dimensional, domain-driven design)
• Deep knowledge of SQL, Python, and distributed data processing frameworks and optimization
• Strong understanding of data governance frameworks (lineage, metadata, cataloging)
• Experience implementing data quality controls and monitoring frameworks
  
  Knowledge of regulatory requirements (BSA/AML, audit, data controls, privacy)
• Expertise in CI/CD pipelines and Dev Ops for data engineering
• Ability to enforce coding standards and engineering best practices
• Executive-level communication and stakeholder management across Product, Technology, Risk, and Business teams.

Demonstrates advanced expertise in Data Engineering, including proficiency in Cloud Data Platforms, Data Architecture, and Data Governance. Capable of leading complex projects and providing strategic guidance to executive leadership while ensuring adherence to industry standards and best practices.

• Cloud Data Platforms (Azure, ADF, Databricks)
• Data Architecture Patterns (Batch, Streaming, Real-Time)
• Data Modeling (Dimensional, Domain-Driven Design)
• SQL and Python Proficiency
• CI/CD Pipelines and Dev Ops for Data Engineering

• Data Engineering
• Data Management
• Data Architecture
• Data Quality Controls
• Data Governance Frameworks
• Distributed Data Processing
• Coding Standards Enforcement
• Data Processing Optimization
• Data Cataloging
• Metadata Management

• Executive-Level Communication
• Stakeholder Management

• BSA/AML
• Audit
• Data Controls
• Privacy
• Information Security