DXC Technology is a leading global technology services provider helping the world's largest enterprises and public sector organizations modernize mission-critical systems, optimize operations, and accelerate innovation through AI, cloud, security, and enterprise technology solutions.
Our Insurance Software and Business Process Solutions (ISB) organization partners with insurers worldwide to transform and manage core insurance operations. By combining deep insurance expertise, market-leading software platforms, and AI-powered solutions, we help clients modernize policy administration, claims, billing, underwriting, and digital engagement across Life & Annuity, Property & Casualty, and Specialty Insurance.
Position Summary
The Data Engineering Lead is responsible for the design, development, governance, and operational excellence of enterprise data platforms, pipelines, and analytics capabilities. This role provides technical leadership for data engineering initiatives while managing a team of engineers responsible for delivering scalable, secure, and reliable data solutions that support business intelligence, AI, machine learning, operational reporting, and digital transformation programs.
The successful candidate combines deep technical expertise with leadership skills to establish enterprise data standards, drive modernization initiatives, implement cloud-native data architectures, and ensure data is treated as a strategic business asset. This individual will partner closely with product management, application engineering, cloud operations, architecture, security, and business leaders to deliver measurable business outcomes.
Data Strategy & Architecture
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.
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Ensure alignment with enterprise architecture, cybersecurity, and compliance requirements.
Data Platform Engineering
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.
Leadership & Team Development
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.
Data Governance & Quality
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.
AI & Advanced Analytics Enablement
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.
Delivery & Execution
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.
Stakeholder Engagement
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.
Education
Bachelor's degree in Computer Science, Information Systems, Engineering, Data Science, or related field.
Master's degree preferred.
Experience
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.
Strong experience in multiple areas including:
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
Preferred Qualifications
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.
Leadership Competencies
Strategic Thinking
Technical Leadership
Decision Making
Stakeholder Management
Talent Development
Executive Communication
Continuous Improvement Mindset
Customer Focus
Results Orientation
Cross-Functional Collaboration
At DXC Technology, we believe strong connections and community are key to our success. Our work model prioritizes in-person collaboration while offering flexibility to support wellbeing, productivity, individual work styles, and life circumstances. We’re committed to fostering an inclusive environment where everyone can thrive.
If you are an applicant from the United States, Guam, or Puerto Rico
DXC Technology Company (DXC) is an Equal Opportunity employer. All qualified candidates will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, pregnancy, veteran status, genetic information, citizenship status, or any other basis prohibited by law. View postings below .
We participate in E-Verify. In addition to the posters already identified, DXC provides access to prospective employees for the Federal Minimum Wage Poster, Federal Polygraph Protection Act Poster as well as any state or locality specific applicant posters. To access the postings in the link below, select your state to view all applicable federal, state and locality postings. Postings are available in English, and in Spanish, where required. View postings below.
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