Sr Data Architect

Role Summary

The Senior Data Architect delivers the data vision and strategy for the organization, as defined by the Chief Data Architect (or equivalent leadership). This role is responsible for the design, governance, and technical oversight of the enterprise data architecture, ensuring that data systems are scalable, secure, compliant, and aligned with core business needs.

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Key Responsibilities1. 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).

2. 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 privacy).

3. 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.

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Required Skills and ExperienceTechnical

• Advanced experience in designing 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.