Data Architect

Key Responsibilities - Enterprise Data Strategy & Client Engagement: - Develop and maintain a comprehensive data architecture strategy that aligns with organizational and client business objectives. - Serve as a key technical advisor for clients, translating business requirements into innovative data solutions. - Build and maintain strong client relationships by providing expert guidance and managing expectations throughout project lifecycles. - Data Modeling, Design & Engineering: - Design and optimize both logical and physical data models to support enterprise-wide systems. - Architect data warehousing solutions, overseeing the integration of data from multiple sources to enable robust business intelligence and analytics. - Directly develop, test, and implement ETL processes and data pipelines, ensuring data quality, consistency, and performance. - Technology Evaluation & Implementation: - Evaluate emerging data technologies and tools to determine their fit within the existing architecture and potential for future scalability. - Oversee the integration of new technologies into the enterprise data architecture, balancing innovation with risk management. - Team Leadership & Hands-On Management: - Lead cross-functional teams, providing mentorship and technical guidance to junior data engineers and architects. - Maintain a hands-on approach by actively participating in coding, design sessions, and troubleshooting complex data issues. - Ensure project milestones are met through effective resource management and team coordination. - Performance, Security & Best Practices: - Optimize data storage, retrieval, and processing performance across various systems. - Collaborate with security teams to enforce data governance, compliance, and privacy standards. - Establish and promote best practices in data management, data engineering, and architecture design. - Documentation & Reporting: - Develop and maintain comprehensive documentation covering data architecture designs, data flows, integration processes, and project status. - Provide regular updates and reports to both internal stakeholders and clients on project progress and system performance. Required Qualifications - Education: - Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Science, or a related field. - Experience: - 10+ years of experience in data architecture, data engineering, or related roles. - Proven experience in designing and implementing enterprise-level data solutions with a hands-on technical approach. - Demonstrated track record of managing client relationships and leading technical teams. - Technical Skills: - Expertise in data modeling, data warehousing, and database design (both relational and NoSQL). - Strong proficiency in data engineering, including experience with ETL tools, data integration frameworks, and big data technologies. - Hands-on experience with cloud data platforms (e.g., Azure, Google Cloud) and modern data processing frameworks. - Familiarity with scripting and programming languages (e.g., Python, SQL,) to support hands-on development and troubleshooting. - Experience with data governance frameworks & solutions ( Informatica, Collibra, Purview etc - Exceptional client management and communication skills, with the ability to interact confidently with both technical and non-technical stakeholders. - Proven team management and leadership abilities, including mentoring, coaching, and project management. - Strong analytical and problem-solving skills with a proactive, detail-oriented approach. - Ability to work collaboratively in a fast-paced, dynamic environment while driving multiple projects to successful completio - Relevant certifications such as Azure Solutions Architect, Certified Data Management Professional (CDMP), or similar credentials.