Sargent & Lundy is a global leader in power and energy consulting, where innovation meets integrity, diversity, and a commitment to quality. We stay at the forefront of today’s opportunities in advanced nuclear power, decarbonization, smart grids, battery energy storage systems, hydrogen applications, electric transportation grids, digital modernization, and more. Our distinctive capabilities provide domestic and international clients and partners with a thoroughly reliable source of comprehensive expertise. Sargent & Lundy offers challenge, growth, flexibility, competitive salaries and benefits.
Position Summary:
We are seeking a strategic Data and AI Architect to lead the design, governance, and implementation of enterprise-grade Data, AI, and ML platforms. This position, as part of the Enterprise Architecture Team, is central to enabling scalable, secure, and resilient infrastructure and data solutions that support advanced analytics, machine learning, and data science throughout Sargent & Lundy. You will drive innovation and ensure our systems align with evolving business needs and best industry practices.
This position offers the flexibility of a hybrid schedule with the expectation of 3 days per week in our Chicago office, and 2 days remote from home.
Key Responsibilities:
Data Architecture Strategy and Planning
- Develop and deliver long-term strategic goals for data architecture vision and standards, collaborating closely with data users, department managers, clients, and other key stakeholders.
- Design short-term tactical solutions supporting long-term objectives and the overall data management roadmap.
- Establish robust processes for governing the identification, collection, and use of corporate metadata, ensuring accuracy and validity.
- Implement effective methods for tracking and improving data quality, completeness, redundancy, and integrity.
- Conduct capacity planning, lifecycle management, usage analysis, feasibility studies, and related tasks to optimize data storage and access.
- Create and maintain strategies for data security, backup, disaster recovery, business continuity, and archiving.
- Ensure all data strategies, architectures, and processes comply with relevant regulatory requirements, industry standards, and S&L Enterprise Architecture Board Reviews.
Data Platform Enablement
- Partner with Data Architecture and Platform teams to implement next-generation data platforms (e.g., Data Fabric, Data Mesh, and Data Governance) that are scalable and secure.
- Define technical standards for data ingestion, transformation, enrichment, and consumption to support advanced analytics and machine learning.
- Ensure secure, governed access to data across platforms such as Databricks, Snowflake, Informatica, Azure Synapse, AWS, and other modern data technologies.
- Oversee integration and interoperability across multiple systems and platforms, minimizing technical debt and maximizing business value.
- Evaluate, design, and implement comprehensive automation strategies across Sargent & Lundy’s Data and AI/ML platforms, driving continuous improvement in metadata management, data quality monitoring, ingestion pipelines, analytics operations, and MLOps processes.
Analytics and Operational Management
- Assess and determine governance, stewardship, and frameworks for managing data across the organization.
- Establish architecture and governance guidelines for dashboard and reporting deployments, supporting scalable analytics solutions.
- Promote standardized data management methodologies and best practices company wide.
- Evaluate, select, and oversee the implementation of tools and systems supporting data technology goals (e.g., ETL/ELT, data lakes, BI/reporting).
- Lead the mapping of data sources, movement, interfaces, and analytics processes to ensure data quality and maximize insight utilization.
- Collaborate with functional leaders, business groups, and project managers on strategic initiatives involving data.
- Troubleshoot and resolve data-related issues related to systems integration, compatibility, and multi-platform coordination.
- Act as a mentor and advocate for data management, providing coaching, training, and career development for staff.
- Develop and implement robust testing criteria to validate fidelity and performance of data architecture solutions.
- Document data architecture standards and environment to maintain a current, accurate representation of the enterprise data landscape.
- Identify opportunities for data reuse, migration, retirement, and rationalization of legacy systems.
AI/ML and Data Science Architecture
- Architect and implement platforms and pipelines for ML model development, deployment, and monitoring.
- Collaborate with Data Scientists and other stakeholders to define feature engineering processes, model lifecycle management, and MLOps best practices.
- Enable and optimize data lakehouse architectures (e.g., Databricks, Snowflake) to support ML and advanced analytics workloads.
- Design scalable infrastructure for real-time and batch inference, ensuring seamless integration with business applications and analytics platforms.
- Evaluate emerging AI/ML technologies and recommend adoption to maintain a cutting-edge technology stack.