Senior Data Engineer I

The Infrastructure Data & Analytics team unifies FinOps, Data Science and Business Intelligence to enable Technology cost transparency, infrastructure performance optimization and commercial efficiency for the enterprise through consistent, high-quality data and predictive analytics. This team within Global Infrastructure aims to establish and reinforce a culture of effective metrics, data-driven business processes, architecture simplification, and cost awareness. Metric-driven cost optimization, workload-specific forecasting and robust contract management are among the tools and practices required to drive accountability for delivering business solutions that derive maximum value. The result will provide a solid foundation for decision-making around cost, quality and speed.

We are seeking an experienced Senior Data Engineer for our team who can lead the design, development and enhancement of our data model and architecture. This team sets the foundation for how infrastructure utilization, consumption and asset inventory data is ingested, validated, and presented in our suite of reporting capabilities. The Sr. Data Engineer will help ensure data quality (data accuracy, completeness, timeliness, consistency, uniqueness and relevance) is meeting the highest standards for our users.  This individual will be responsible for implementing our target data architecture, leveraging best practices for data management, automating data feeds and transformations, and maintaining excellent documentation.

Lets build on what you know.

The role will require a unique blend of strong data ops technical and design skills to translate business decisions into data requirements.  This individual will build a deep understanding of the infrastructure data we use in order to work across the ID&A team and key stakeholders the appropriate data to tell a data story. This includes implementing and maintaining a data architecture that follows data management best practices for ensuring data ingestion, transformation, storage and analytics are handled according to their specific purpose using the appropriate tools: ingestion captures raw data without applying business logic, transformation processes data discretely for auditability, and analytical queries retrieve structured outputs without relying on upstream processes. They will bring passion for data-driven decisions, enterprise solutions, and collaboration to the role, transforming platform data into actionable insights by utilizing data engineering and data visualization best practices.

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
• Bachelor’s Degree in computer science, computer science engineering, data engineering, or related field required; advanced degree preferred