Senior Data Engineer

Key responsibilities include:

• Data Architecture: Perform all technical aspects of data architecture and database management for ID&A, including developing data pipelines, new database structures and APIs as applicable
• Data Design: Translate logical data architectures into physical data designs, ensuring alignment with data modeling best practices and standards
• Data Process and Monitoring: Ensure proper data ingestion, validation, testing, and monitoring for ID&A data lake
• Support database and data platform administration for initiatives building, enhancing, or maintaining databases, data warehouses and data pipelines
• Data Migration: Design and support migration to a data model that is independent of the particular technologies or tools used for storing, processing, or accessing the data
• Data Integrity: Ensure the accuracy, completeness, and quality of data is maintained over time regardless of upstream systems or downstream 
• Agile Methodologies: Function as a senior member of an agile feature team and manage data assets as per the enterprise standards, guidelines and policies
• Partner closely with business intelligence team to capture and define data requirements for new and enhanced data visualizations
• Work with product teams to prioritize new features for ongoing sprints and manage backlog
• Enterprise Thinking: Partner with data architects and engineers across Global Infrastructure and Asset Management teams to evolve the broader tech operations data architecture landscape
• Mentor junior data engineers through ongoing development efforts and enforcement of SDLC standards
• Act as point of contact for data-related inquiries and data access requests
• Contribute to decisions about tools, methods and approaches
• Innovation: Leverage the evolving technical landscape as needed, including AI, Big Data, Machine Learning and other technologies to deliver meaningful business insights

Minimum Requirements:

• 8+ years of DataOps engineering experience in implementing pipeline orchestration, data quality monitoring, governance, security processes, and self-service data access  
• Experience managing databases, ETL/ELT pipelines, data lake architectures, and real-time processing
• Proficiency in API development and stream processing frameworks
• Hands-on coding experience in Python
• Hands-on expertise with design and development across one or more database management systems (e.g. SQL Server, PostgreSQL, Oracle)
• Testing and Troubleshooting: Ability to test, troubleshoot, and debug data processes
• Strong analytical skills with a proven ability to understand and document business data requirements in complete, accurate, extensible and flexible logical data models, data visualization tools (e.g. Apptio BI, PowerBI)
• Ability to write efficient SQL queries to extract and manipulate data from relational databases, data warehouses and batch processing systems
• Fluent in data risk, management, and compliance terminology and best practices
• Proven track record for managing large, complex ecosystems with multiple stakeholders
• Self-starter who is able to problem-solve effectively, organize and document processes, and prioritize feature with limited guidance
• An enterprise mindset that connects the dots across various requirements and the broader operations/infrastructure data architecture landscape
• Excellent influential and collaboration skills; ability to drive consensus and tangible outcomes, demonstrated by breaking down silos and fostering cross-team communication
• Understanding of complex software delivery including build, test, deployment, and operations; conversant in AI, Data Science, and Business Intelligence concepts and technology stack
• Foundational Public Cloud (AWS, Google, Microsoft) certification; advanced Public Cloud certifications a plus
• Experience working in technology business management, technology infrastructure or data visualization teams a plus
• Experience with design and coding across multiple platforms and languages a plus
• Bachelors Degree in computer science, computer science engineering, data engineering, or related field required; advanced degree preferred