Data Architect

Location: Bengaluru

Requirements:
At least 10 years of experience in IT or Software Engineering
Proven experience as a Data Architect or in a similar role, with a strong track record of designing and implementing transactional and analytical data architectures.
Proficient in data modeling techniques, data integration methodologies, and data management principles.
Extensive knowledge of database systems, modern data warehousing, data lake and data storage technologies.

Experience with cloud-based data platforms and technologies (e.g., Azure, AWS, GCP) is essential.
Strong analytical and problem-solving skills, with the ability to translate business requirements into technical solutions.
Highly detail oriented with excellent communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at all levels.
Familiarity with data governance, data security, and data privacy regulations.
Good understanding of data protection standards and associated security processes.

Data Strategy and Architecture:
Develop and maintain the company's data strategy, ensuring alignment with business goals and objectives.
Design, implement, and oversee the overall data architecture, including data integration, data modeling, data storage, and data access.

Data Standards and Policies:
Establish, enforce, and maintain data standards, naming conventions, business glossaries, data and report catalogs and data management best practices.
Develop and maintain data policies and procedures to ensure compliance with regulatory requirements.

Data Modeling and Design:
Design and create conceptual, logical, and physical data models that meet business requirements and support efficient data management.
Collaborate with business stakeholders, data scientists, and developers to understand data needs and design appropriate data structures.

Data Integration and Management:
Define data integration strategies and ensure seamless data flow across systems and applications.
Implement data governance practices, including data quality, data lineage, and data security.

Data Storage and

Infrastructure:
Optimize data storage and retrieval mechanisms for performance, scalability, and reliability.
Collaboration and Leadership:
Collaborate with cross-functional teams, including developers, business analysts, and project managers, to drive successful data-related initiatives.
Provide technical guidance and mentorship to junior data team members.