Data Engineering Architect

The Data Engineering Architect will lead the end-to-end architecture, design, and technical execution of data modernization initiatives across cloud, application, and data platforms. This role is responsible for defining scalable data architectures, guiding engineering teams, and ensuring successful migration, integration, and modernization of enterprise data ecosystems., Architecture & Technical Leadership

• Define the target-state data architecture spanning ingestion, transformation, storage, and consumption layers across cloud platforms.
• Lead the modernization of data pipelines, data platform components, and application-data integration patterns.
• Provide architectural guidance for cloud-native services, data engineering frameworks, and analytics/AI readiness.
• Establish best practices for data modeling, schema design, metadata, governance, and lineage.

Data Engineering & Migration Leadership

• Oversee large-scale data migration, ETL/ELT modernization, and pipeline re-engineering efforts.
• Direct design and optimization of ingestion frameworks, workflow orchestration, dependency management, and distributed compute architecture.
• Ensure data reliability, performance, and SLAs through technical assessments and optimization strategies.
• Evaluate and modernize legacy data systems, frameworks, and integrations.

Cloud & Platform Alignment

• Work with cloud architects to align data architecture with infrastructure standards, security policies, RBAC, and governance frameworks.
• Drive adoption of cloud-native services such as storage, compute, serverless, AI search, logging, and monitoring.

Collaboration & Cross-Team Alignment

• Partner with application architects, cloud teams, and business/analytics stakeholders to ensure seamless end-to-end data flows.
• Work closely with SMEs to validate business rules, ingestion requirements, and domain-specific models.
• Provide technical direction to engineering teams, ensuring consistency with architectural principles.

Quality, Governance & Security

• Ensure adherence to data governance, quality, compliance, and privacy requirements (including PII/PHI constraints).
• Define standards for data lifecycle management, observability, and operational excellence.
• Review and validate requirements, test strategies, and implementation plans.

Documentation & Communication

• Produce architectural diagrams, technical designs, migration plans, and data flow documentation.
• Communicate complex technical concepts to engineering teams, architects, and business stakeholders.
• Support UAT, production readiness, and handover activities during deployment phases.

• Strong background in data engineering, cloud-native data services, ETL/ELT frameworks, and distributed data platforms.
• Extensive experience designing and modernizing data architectures on cloud environments (Azure/AWS/GCP).
• Proficiency with modern data stacks: Spark, Synapse/Databricks, Kafka/Event streams, SQL/NoSQL, Lakehouse platforms.
• Understanding of application-data architectures, integration patterns, and DevOps/CI-CD processes.
• Ability to lead technical teams, troubleshoot complex data problems, and drive best practices across engineering functions.

Skills: Acceptance Testing, Amazon Web Services (AWS), Application Integration, Architectural Services, Artificial Intelligence (AI), Best Practices, Cloud Applications, Cloud Architecture, Cloud Computing, Computer Architecture, Continuous Deployment/Delivery, Continuous Integration, Data Management, Data Migration, Data Modeling, Database Design, Database Extract Transform and Load (ETL), DevOps, Documentation, Ecosystems, GCP (Good Clinical Practices), Identify Issues, Leadership, Maintain Compliance, Metadata, Microsoft Windows Azure, Multiplatform/Cross-Platform, NoSQL, Production Support, Regulatory Compliance, Requirements Validation/Verification, SQL (Structured Query Language), Service Level Agreement (SLA), Software Engineering, Standards Development, Strategic Planning, System Migration, Team Lead/Manager, Technical Analysis, Technical Leadership, Technical/Engineering Design, Test Requirements, Test Strategy

Since 2004, Anblicks has been helping customers across the globe, enabling them with digital transformation services. Anblicks specialized in delivering Big Four consulting experience to mid-size enterprises. Anblicks employs more than 400 technology professionals and over 100 data analysts and data science experts. With a focus on Logistics, Healthcare, BFSI and Retail industries, Anblicks continues to drive technology innovation while providing customers with world-class levels of services and support. Anblicks is headquartered in Dallas, Texas with additional offices in other U.S. states, Canada and India.

Company Size: 1,500 to 1,999 employees