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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