Lead Data Engineering Architect – Insurance

DXC Technology; New York (NY); Híbrido; USD 180.000 - 240.000; Jornada completa

Descripción de la vacante

DXC Technology is seeking a Data Engineering Lead to design, govern, and operate enterprise data platforms supporting BI, AI, and analytics initiatives. You will lead a team of engineers, set data standards, and drive modernization across cloud-native architectures while partnering with product, security, and business leaders.

The role emphasizes data as a strategic asset, driving measurable business outcomes and ensuring compliance, scalability, and operational excellence across global delivery

Formación

• Experience designing and delivering enterprise data platforms.
• 10+ years in Data Engineering or related tech disciplines.
• 3+ years leading technical teams or large data initiatives.
• Experience with cloud data architectures and governance.
• Strong collaboration with product, security, and leaders.

Responsabilidades

• Define enterprise data strategy and roadmaps for engineering.
• Lead data platform design, pipelines, and governance.
• Mentor Data Engineers, Architects, and integration specialists.
• Drive DataOps, IaC, and automation for reliable delivery.
• Partner with stakeholders to align data investments with business goals.

Conocimientos

SQL

Python

Spark

ETL/ELT

Data Lakes

Data Warehouses

Cloud (Azure/AWS)

Educación

High school diploma or GED

Bachelor's degree in CS/IS/Engineering

Master's degree preferred

Herramientas

Databricks

Snowflake

Synapse

Redshift

BigQuery

CI/CD

IaC

Descripción del empleo

Job Description:

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.

Key Responsibilities

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.
• 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.

Required Qualifications

Education

• High school diploma or GED (required).
• Bachelor's degree in Computer Science, Information Systems, Engineering, Data Science (Preferred).
• 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.

Technical Expertise

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.

Disability Accommodations

If you are an individual with a disability, a disabled veteran, or a wounded warrior and you are unable or limited in your ability to access or use this site as a result of your disability, you may request a reasonable accommodation by contacting us via email.

Please note: DXC will respond only to requests for accommodations due to a disability.

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.

Postings Link