Senior Data Architect

Role Description:

The Senior Data Architect will be responsible for designing, developing, and deploying robust, scalable, and efficient data architectures for bidding and development phases. This role requires extensive experience in data modeling, database design, and data integration. The ideal candidate will have a strong background in data management and a deep understanding of modern data technologies and best practices.

Key Responsibilities:

Pre-sales Support: Take charge of solution development, work breakdown structure development and corresponding estimation in bidding phase.
Architectural Design: Design and develop comprehensive data architecture strategies that align with business goals.
Solution Development: Lead the design, implementation, and maintenance of data models, databases, and data integration solutions.
Collaboration: Collaborate with stakeholders to understand data requirements and translate them into technical specifications.
Security and Compliance: Ensure data architecture solutions are scalable, secure, and optimized for performance.
Governance: Develop and enforce data governance policies and standards.
Technical Leadership: Provide technical leadership and mentorship to data engineering teams.
Customer Engagement: Act as the primary point of contact for external customers and stakeholders, understanding their needs and requirements.
Data Quality Management: Conduct data quality assessments and implement data quality improvement initiatives.
Issue Resolution: Troubleshoot and resolve complex data-related issues.
Industry Awareness: Stay up-to-date with the latest industry trends and technologies, and proactively recommend improvements and innovations.

Qualifications:

Bachelors or Masters degree in Computer Science, Information Technology, or a related field.
Extensive experience as a Data Architect or in a similar role.
Proficiency in data modeling, database design, storage, and data integration.
Strong understanding of data security, data governance, and data integration.
Proven track record of designing and implementing large-scale data solutions.
Strong knowledge of SQL and NoSQL databases.
Experience with data warehousing solutions such as Snowflake, Redshift, or BigQuery.
Excellent problem-solving and analytical skills.
Strong communication and collaboration abilities.
Relevant certifications (e.g., Certified Data Management Professional, AWS Certified Big Data) are a plus.

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