Data Architect

Job Summary

The Data Architect works closely with business, analytics, and IT teams to develop scalable data models, define data standards, and enable enterprise-wide data initiatives.

Roles and Responsibilities:

• Design and maintain the enterprise data architecture, ensuring alignment with business and analytics strategies.
• Define data modeling standards, metadata management practices, and data lifecycle policies.
• Define and evolve the data architecture roadmap to support data modernization, cloud adoption, and AI/ML initiatives.
• Recommend technology solutions and platforms (e.g., data lakes, warehouses, real-time data processing) based on business needs.
• Stay current with trends in data architecture, data mesh, data fabric, and emerging data technologies.
• Partner with business units, data analysts, and data scientists to translate business requirements into data solutions.
• Work with application and infrastructure teams to ensure data architecture supports performance, scalability, and resiliency needs.
• Collaborate with the Enterprise Architecture and Cloud teams to ensure end-to-end architectural alignment.
• Define data governance frameworks, standards, and policies in partnership with Data Governance teams.
• Ensure compliance with data privacy regulations (e.g., GDPR, CCPA) and internal security standards.
• Conduct architecture reviews to assess adherence to data quality, lineage, and integrity requirements.
• Design strategies for seamless integration of data across systems, including cloud, on-premise, and third-party platforms.
• Enable interoperability across business units by defining shared data definitions and interfaces.
• Develop and maintain data APIs and pipelines to ensure reliable data exchange.
• Work closely with cybersecurity teams to implement robust data protection measures.
• Assess and mitigate risks related to data loss, data breaches, and system failures.
• Ensure secure access and role-based permissions for enterprise data assets.
• Identify opportunities to optimize data flows, storage, and processing using automation and modern tools.
• Foster a data-driven culture by enabling self-service analytics and trusted data assets.
• Support advanced analytics, AI, and machine learning by ensuring a solid data foundation.
• Develop and maintain comprehensive data architecture documentation, including models, glossaries, and data dictionaries.
• Contribute to enterprise standards, best practices, and reusable data architecture patterns.

Position Requirements:

• Bachelor’s degree in Computer Science, Data Science, Information Systems, or a related field (Master’s preferred).
• Relevant certifications such as: o Certified Data Management Professional (CDMP) o AWS Big Data or Data Analytics Specialty o Microsoft Azure Data Engineer Associate o Google Cloud Professional Data Engineer o TOGAF (preferred for enterprise alignment) Experience
• Minimum of 8 years in data architecture, data engineering, or enterprise data management roles.
• Proven experience designing large-scale data platforms, data lakes, and warehouses (e.g., Snowflake, Redshift, BigQuery).
• Strong background in data modeling, ETL/ELT, data integration, and metadata management. Skills and Competencies
• Deep understanding of data architecture principles and best practices.
• Proficiency in modern data technologies and languages (e.g., SQL, Python, Spark, Kafka, DBT).
• Strong analytical, problem-solving, and decision-making skills.
• Excellent communication and collaboration abilities to work across technical and business teams.