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.

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