Sr Data Architect (Local to Hartford, CT/Minneapolis, MN)

Key Responsibilities: Data Architecture & Design Data Modeling: Design, maintain, and evolve comprehensive data models (Conceptual, Logical, and Physical) for core business services and platforms. Data Flow: Define and create data flow diagrams and orchestration strategies, ensuring efficient and governed data movement between up- and downstream systems. System Alignment : Collaborate closely with Application and Cloud Architects to ensure the organization s technical systems are designed to fully support the established data architecture standards. Technology Selection: Develop product short-lists and evaluation criteria for selecting data architecture components, such as data warehousing solutions, Big Data platforms (e.g., Hadoop, Spark, Kafka), and database technologies (SQL/NoSQL). Data Governance & Quality Governance Frameworks: Evolve and define data governance policies, standards, and best practices across the organization. Metadata Management: Design, support, and manage data dictionaries, metadata repositories, and common entities to ensure consistent use and definition of data. Data Quality: Drive the standards for Data Quality across multiple datasets, ensuring consistency and data trust across the enterprise. Compliance: Design data retention, upgrade, management, decommission, and archive strategies in compliance with data policies and regulatory standards (e.g., data ). Technical Leadership & Mentorship Oversight: Provide technical oversight, advice, and guidance to other Data Architects, Data Engineers, and development teams regarding data structures and associated components. Standard Enforcement: Ensure project teams adhere to the corporate data standards and architectural principles set by data leadership. Mentorship: Mentor and support colleagues in multi-disciplinary teams, promoting best practices in data architecture and design. Required Skills and Experience Technical Advanced experience in deg and implementing data models (Star Schema, Snowflake, etc.). Expertise in a wide variety of database technologies, including relational (SQL) and NoSQL platforms, and Big Data technologies. Demonstrated ability to architect scalable, high-performance data warehousing and data lake solutions on major cloud platforms (e.g., AWS, Azure, Google Cloud Platform). Strong understanding of ETL/ELT tools, data integration strategies, and advanced data processing techniques. Professional Communication: Excellent verbal and written communication skills with the ability to translate complex technical information and language into simple, accessible terms for non-technical stakeholders. Leadership: Strong leadership skills with the proven ability to establish relationships, manage differing stakeholder perspectives, and drive technical direction across teams. Strategic Thinking: A systematic, disciplined, and analytical approach to problem-solving, with an awareness of evolving business needs and technology capabilities.