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How will you make an impact in this role?
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 Solutions Architect for our team who can support the design, development and enhancement of our data model and architecture. This DataOps 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 Solutions Architect will help ensure our data architecture integrates seamlessly with other Technology platforms and optimizes performance with best architecture standards. This individual will be responsible for setting the strategy for our target data architecture, collaborating across Tech and business partners, leveraging best practices for risk and data management, and optimizing cross-platform integration.
Let s build on what you know.
The role will require a unique blend of strong data ops technical and leadership 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 designing and implementing a data architecture that follows enterprise architecture and 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 act as a key point of contact with upstream and downstream partner teams to ensure data is ingested and provided in a consistent and repeatable way. 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 solutions architecture for ID&A, including integrating data sources, defining appropriate data environments strategies, and enforcing API (Application Programming Interface) standardization as applicable
- Data Design: Translate logical data architectures into physical data designs, ensuring alignment with data modeling best practices and platform blueprints
- Data Process and Monitoring: Ensure proper data ingestion, validation, testing, and monitoring for ID&A data lake
- Leads design and code reviews to ensure the delivery of best-in-class data analytics and adherence to enterprise standards
- 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: Act as the platform s single point of contact (SPOC) when coordinating with relevant stakeholders and supervising the data architecture implementation
- Identifies and implements technical solutions and business process improvements by analyzing business needs and leveraging innovative technologies
- Ensures the engineered environment meets the specification in terms of business requirements, application design and infrastructure requirements, i.e. accountable for the platform integration performance and efficiency
- Enterprise Thinking: Partner with data architects and engineers across Global Infrastructure and Asset Management teams to evolve the broader tech operations data architecture landscape
- Responsible for coaching and mentoring engineering resources on solution architecture, providing advice, mentorship and assistance to less experienced colleagues as required
- Contribute to decisions about new technologies, 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
- Ensures accurate asset information and architecture decisions are well-documented in the appropriate systems and repositories
Minimum Requirements:
- 10+ years of solutions architecture, data architecture or DataOps engineering experience in designing pipeline orchestration, data quality monitoring, governance, security processes, and self-service data access
- Prior experience in multiple IT disciplines with a confirmed understanding of architectural concepts (business, data, technical and solution) and real-time processing
- Extensive experience using a systems analysis and design methodology that is applicable to an agile product environment
- Advanced to authoritative level knowledge and understanding of solution architecture, complex application systems design and platform integration via modern approaches (i.e. RESTful APIs)
- Ability to perform system design reviews to ensure selection of appropriate technology, efficient use of resources, and alignment to strategic platform roadmaps
- Full understanding of Service Oriented Architecture design principles, execution patterns and performance optimization techniques
- Able to participate in the prevention, diagnosis, and resolution of system outages as a leader in the underlying architecture
- Hands-on coding experience in Python
- Hands-on expertise with design and development across one or more database management systems (e.g. GCP, SQL Server, PostgreSQL, Oracle)
- Strong analytical skills with a proven ability to understand and document business data requirements into 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 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
