Senior Data Architect

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 privacy).
• 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 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, GCP).
• 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.

Company Information

Vytwo Technologies is a global leader in enterprise application integration, delivering end-to-end IT consulting and business services for mid to large-scale organizations. We offer a comprehensive suite of solutions including business and technology consulting, Cloud, e-business and digital transformation services, system integration, custom application development, re-engineering, and long-term application support.