Our client is seeking a senior-level Data Architect to lead the design and advancement of a modern enterprise data ecosystem that delivers secure, reliable, and scalable access to trusted data across the organization. This role will play a critical part in supporting enterprise transformation by enabling high-quality data integration, governance, and accessibility for business operations, analytics, and digital initiatives.
This individual will define architectural standards, guide data platform evolution, and ensure alignment between business objectives and technology solutions. The ideal candidate combines strategic thinking with hands-on technical expertise and excels in collaborative environments that span multiple teams and disciplines.
Key Responsibilities Data Architecture and Strategy Define and maintain enterprise data architecture, standards, and best practices to support scalable and secure data platforms. Develop and execute architectural roadmaps that modernize legacy data environments and enable advanced analytics and digital capabilities. Establish consistent data models, integration frameworks, and governance practices across enterprise systems. Partner with business and technology stakeholders to ensure data architecture supports operational and strategic needs. Platform Design and Data Integration
Architect and implement scalable data solutions supporting data warehouses, data lakes, and modern lakehouse environments. Design and maintain logical and physical data models that support enterprise applications and reporting needs. Develop and optimize batch and real-time data pipelines, including event-driven and change data capture integrations. Enable efficient data sharing and consumption across operational, analytical, and external systems. Ensure data platforms meet requirements for scalability, performance, reliability, and security. Data Quality, Governance, and Compliance
Establish processes to ensure data integrity, consistency, and accuracy across enterprise systems. Perform data profiling, mapping, lineage tracking, and transformation design. Support enterprise data governance policies, including data classification, stewardship, and lifecycle management. Ensure compliance with regulatory and security requirements governing enterprise data usage. Leadership and Cross-Functional Collaboration
Provide architectural leadership and technical guidance to data engineering and development teams. Collaborate with business leaders, engineers, and analysts to translate requirements into scalable technical solutions. Support agile teams by contributing to solution design, implementation planning, and quality assurance. Identify opportunities to improve data platform efficiency, automation, and scalability. Document architecture, integration patterns, and operational processes to support long-term sustainability.
Required Qualifications
15+ years of experience in data architecture, data engineering, or related technical roles. Extensive experience designing enterprise-scale data platforms, integration frameworks, and data models. Strong expertise with relational databases, distributed data systems, and modern data platform architectures. Proven experience building and optimizing data pipelines supporting large-scale data processing. Experience working with cloud-based data services and modern data platforms such as Databricks, Snowflake, Amazon Redshift, or similar technologies. Strong SQL expertise and deep understanding of data structures, modeling, and performance optimization. Experience with ETL/ELT tools and modern data integration solutions. Solid understanding of data governance, quality management, and enterprise data lifecycle practices. Proven ability to collaborate across technical and business teams to deliver enterprise data solutions. Strong analytical thinking and problem-solving capabilities.
Preferred Qualifications
Experience designing lakehouse, cloud-native, or hybrid data architectures. Background in regulated industries such as financial services, healthcare, or insurance. Experience with real-time data streaming and change data capture technologies. Familiarity with enterprise data modeling tools. Experience integrating SaaS applications into centralized data platforms. Experience working in agile or large-scale enterprise environments. Strong communication skills and ability to influence technical and business stakeholders.
Key Responsibilities Data Architecture and Strategy Define and maintain enterprise data architecture, standards, and best practices to support scalable and secure data platforms. Develop and execute architectural roadmaps that modernize legacy data environments and enable advanced analytics and digital capabilities. Establish consistent data models, integration frameworks, and governance practices across enterprise systems. Partner with business and technology stakeholders to ensure data architecture supports operational and strategic needs. Platform Design and Data Integration
Architect and implement scalable data solutions supporting data warehouses, data lakes, and modern lakehouse environments. Design and maintain logical and physical data models that support enterprise applications and reporting needs. Develop and optimize batch and real-time data pipelines, including event-driven and change data capture integrations. Enable efficient data sharing and consumption across operational, analytical, and external systems. Ensure data platforms meet requirements for scalability, performance, reliability, and security. Data Quality, Governance, and Compliance
Establish processes to ensure data integrity, consistency, and accuracy across enterprise systems. Perform data profiling, mapping, lineage tracking, and transformation design. Support enterprise data governance policies, including data classification, stewardship, and lifecycle management. Ensure compliance with regulatory and security requirements governing enterprise data usage. Leadership and Cross-Functional Collaboration
Provide architectural leadership and technical guidance to data engineering and development teams. Collaborate with business leaders, engineers, and analysts to translate requirements into scalable technical solutions. Support agile teams by contributing to solution design, implementation planning, and quality assurance. Identify opportunities to improve data platform efficiency, automation, and scalability. Document architecture, integration patterns, and operational processes to support long-term sustainability.
Required Qualifications
15+ years of experience in data architecture, data engineering, or related technical roles. Extensive experience designing enterprise-scale data platforms, integration frameworks, and data models. Strong expertise with relational databases, distributed data systems, and modern data platform architectures. Proven experience building and optimizing data pipelines supporting large-scale data processing. Experience working with cloud-based data services and modern data platforms such as Databricks, Snowflake, Amazon Redshift, or similar technologies. Strong SQL expertise and deep understanding of data structures, modeling, and performance optimization. Experience with ETL/ELT tools and modern data integration solutions. Solid understanding of data governance, quality management, and enterprise data lifecycle practices. Proven ability to collaborate across technical and business teams to deliver enterprise data solutions. Strong analytical thinking and problem-solving capabilities.
Preferred Qualifications
Experience designing lakehouse, cloud-native, or hybrid data architectures. Background in regulated industries such as financial services, healthcare, or insurance. Experience with real-time data streaming and change data capture technologies. Familiarity with enterprise data modeling tools. Experience integrating SaaS applications into centralized data platforms. Experience working in agile or large-scale enterprise environments. Strong communication skills and ability to influence technical and business stakeholders.