Hybrid Data Architect na Artefact

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.