Note: The job is a remote job and is open to candidates in USA. DXC Technology is hiring a Lead Data Engineering Architect – Insurance to provide technical leadership for enterprise data platforms, pipelines, governance, and analytics capabilities. The role leads a team delivering secure, scalable data solutions and drives data modernization, cloud-native architecture, AI enablement, and operational excellence.

Responsibilities

• Define and drive the enterprise data engineering strategy and roadmap
• Design scalable data architectures supporting operational, analytical, and AI workloads
• Establish standards for data modeling, data integration, metadata management, and data lifecycle management
• Lead modernization efforts from legacy data environments to cloud-native data platforms
• Ensure alignment with enterprise architecture, cybersecurity, and compliance requirements
• Lead the design and implementation of enterprise data platforms utilizing cloud technologies and modern data architectures
• Develop and maintain high-volume batch, streaming, and event-driven data pipelines
• Build and manage data lakes, data warehouses, lakehouse architectures, and data products
• Establish reusable frameworks and accelerators that improve engineering velocity and solution consistency
• Drive platform automation through Infrastructure-as-Code and DataOps practices
• Lead and mentor a team of Data Engineers, Data Architects, and Data Integration specialists
• Establish engineering best practices and technical standards
• Provide technical oversight, architecture reviews, and design guidance across projects
• Foster a culture of innovation, accountability, continuous learning, and operational excellence
• Support recruitment, onboarding, career development, and performance management activities
• Implement enterprise data governance practices
• Establish data quality frameworks, monitoring, observability, and remediation processes
• Partner with data stewards and business stakeholders to improve trust in enterprise data assets
• Ensure compliance with regulatory, privacy, retention, and security requirements
• Define and monitor KPIs related to data quality, availability, and reliability
• Build and optimize data environments that support AI, machine learning, and advanced analytics initiatives
• Collaborate with data scientists and AI teams to operationalize models and data products
• Support enterprise AI initiatives through governed, trusted, high-quality data pipelines
• Establish patterns for feature engineering, model data preparation, and data consumption
• Manage delivery of multiple concurrent data engineering initiatives
• Create project plans, estimates, resource forecasts, and delivery commitments
• Drive agile delivery practices while maintaining governance and quality expectations
• Identify risks, dependencies, technical debt, and remediation plans
• Ensure predictable delivery, operational stability, and stakeholder satisfaction
• Work closely with executive leadership to align data investments with business objectives
• Partner with engineering, product management, operations, and business teams to prioritize initiatives
• Present technical recommendations, investment strategies, and progress updates to leadership audiences
• Act as a trusted advisor for enterprise data strategy and modernization initiatives

Skills

• High school diploma or GED (required)
• 10+ years of experience in Data Engineering, Data Architecture, or related technology disciplines
• 3+ years leading technical teams or enterprise-scale data initiatives
• Demonstrated experience designing and delivering enterprise data platforms
• Experience leading cross-functional teams in global delivery environments
• SQL and advanced database technologies
• Python, Spark, Scala, or similar data engineering technologies
• ETL and ELT frameworks
• Data Lakes, Lakehouse, and Data Warehouse architectures
• Cloud platforms (Azure, AWS, or Google Cloud)
• Databricks, Snowflake, Synapse, Redshift, BigQuery, or equivalent technologies
• Real-time data processing and streaming architectures
• API-based integration and event-driven architectures
• CI/CD, DataOps, Infrastructure-as-Code, and automation practices
• Strategic Thinking
• Technical Leadership
• Decision Making
• Stakeholder Management
• Talent Development
• Executive Communication
• Continuous Improvement Mindset
• Customer Focus
• Results Orientation
• Cross-Functional Collaboration
• Bachelor's degree in Computer Science, Information Systems, Engineering, Data Science (Preferred)
• Master's degree preferred
• Insurance industry experience
• Experience supporting AI, Machine Learning, and Generative AI initiatives
• Experience implementing enterprise data governance programs
• Success leading large-scale cloud migration or data modernization programs
• Experience with observability, operational monitoring, and reliability engineering

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