For this U.S. based position, the expected compensation range is $112,000 - $168,000 per year, which includes base pay and short-term incentive.

The compensation range for this full-time position applies to candidates located within the United States. Our salary ranges are determined by reviewing roles of similar responsibility and level. Within the salary range, individual pay is determined by several factors including performance, knowledge, job-related skills, experience, and relevant education or training. Schneider Electric also offers a comprehensive benefits package to support our employees, inclusive of medical (with member reward points), dental, vision, and basic life insurance, Benefit Bucks (credits to apply towards your benefits) flexible work arrangements, paid family leaves, 401(k) + match, well-being and recognition (including service anniversary) programs, 12 holidays per year, 15 days of paid time off per year (pro-rated in the first year of employment based on start date), opportunity to purchase company stock (eligibility depends on start date), and military leave benefits.

• Data Strategy Development: Lead the creation and execution of a comprehensive data strategy that aligns with the organization's objectives, including data policies, standards, governance, and lifecycle management.
• Cloud Data Architecture Development: Design and implement cloud-based data solutions, leveraging services such as AWS, Azure, or Google Cloud to build scalable and resilient data architectures that support distributed data storage and processing.
• Design and Implement Data Solutions: Architect high-performing database structures, data warehouses, and data lakes, ensuring they cater to both present and future business requirements and align with the data strategy and business goals.
• Data Management and Governance: Establish robust governance frameworks to ensure data accuracy, quality, security, and compliance with internal and external regulations.
• Data Distribution Strategy: Develop strategies for data distribution that ensure data availability, consistency, and fault tolerance across multiple geographic locations and platforms.
• Data Access Patterns: Define and implement efficient data access patterns and strategies to optimize for various use cases, such as transactional workloads, analytical processing, and real-time data access.
• Advanced Data Integration Techniques: Utilize modern data integration techniques, including streaming data pipelines and event-driven architectures, to facilitate real-time data processing and insights.
• Performance Tuning: Optimize data systems for performance and scalability, ensuring they support the data strategy and business intelligence needs.
• Data Security and Compliance: Implement comprehensive data security policies and procedures that align with the data strategy and protect the organization's data assets.
• Technology Evaluation and Adoption: Continuously assess and recommend new data technologies and data management tools that can enhance the data strategy and architecture.
• Collaboration with Stakeholders: Work closely with business leaders and IT teams to translate business needs into actionable data architectures that support and enhance business value.
• Documentation and Communication: Effectively document the data architecture and strategy and communicate these concepts to ensure understanding and adherence to strategic objectives.
• Mentoring and Leadership: Provide leadership in data-related areas of expertise, mentor junior staff, and foster a culture that supports the data strategy.

• Contribute to Schneider Electric's Sustainability Business technology strategy with a focus on Data Architecture.
• Establish and promote data architecture principles, standards, and best practices.
• Provide technical mentorship and educate peers on best practices, technology trends, tools, and techniques.
• Champion a structured data architecture governance model for robust application design.
• Develop strategic roadmaps in partnership with business and tech leaders, considering budget, resource, and technical constraints.

• Education: Bachelor's degree in computer science, information technology, or related field; master's degree in data science or a related field preferred.
• Experience: 5-8+ Years Experience in data and data architecture related roles. Extensive experience in data architecture, with a strong foundation in both relational databases and modern cloud data architectures, including big data technologies and data pipeline tools.
• Technical Skills: Proficiency in SQL, database platforms (e.g., MySQL, Oracle, SQL Server), data warehousing, ETL processes, data modeling tools, and familiarity with cloud services (AWS, Azure, Google Cloud), big data technologies (Hadoop, Spark), and data pipeline tools (Apache Kafka, NiFi).
• Strategic Thinking: Ability to craft and execute a data strategy that integrates data analytics, data science, and machine learning to support business objectives and foster innovation.
• Analytical Skills: Strong analytical skills to solve complex problems, leverage data science techniques, and make informed decisions based on data analysis.
• Communication Skills: Excellent communication and interpersonal skills to articulate complex data strategies and collaborate effectively with stakeholders and cross-functional teams.