VP, Data Architect

Pacific Life • Charlotte, NC

1d

About The Position

Pacific Life is investing in bright, agile and diverse talent to contribute to our mission of innovating our business and creating superior customer experience. We’re actively seeking a talented VP Enterprise Data Architect to join our Corporate Technology team in Charlotte, NC. As a VP Enterprise Data Architect, you will set the direction and vision for the technologies that support various business units at Pacific Life, architecting an AI-first data ecosystem that bring Pacific Life to the AI age . You will manage the architecture, design, development, and implementation of data solutions that satisfy the business requirements and fit the data strategy . You will guide a team of data architects and work with data engineers, data analysts, data scientists, and other partners to produce high-quality, scalable, and trustworthy data products. You will also make sure that the data architecture practices, standards, and approaches are adhered to and refined. You will cultivate a data owner’s mindset and will ensure standard tools and patterns are leveraged across the enterprise. How you will make an impact: Manage the data architecture team and provide technical guidance, mentorship, and feedback. Define and execute the data architecture roadmap and vision, in alignment with the data strategy and business objectives. Design and implement data solutions that leverage modern technologies, such as cloud, streaming, and machine learning. Establish and enforce the data architecture defined patterns, tools and technologies. This includes data sourcing, landing, transformation, and data access capabilities. In addition, working with the Enterprise Architecture team to adhere to Enterprise Architecture standards and patterns. Participate in troubleshooting the data environment issues and incidents and provide expertise to support root cause analysis and resolution. Evaluate and recommend new data tools, technologies, and frameworks, and conduct proof of concepts and pilots with the Data Engineering team. Communicate and present the data architecture strategies and solutions to various audiences, such as senior management, business users, and technical teams. Architect and Design Data Platforms: Overseeing the design and implement scalable, cloud-based data architectures, enabling real-time and batch data processing to support analytics, AI/ML, and business intelligence use cases. Data Integration: Lead efforts to integrate diverse data sources (structured, semi-structured, and unstructured), ensuring data consistency, quality, and availability across hybrid environments (cloud and on-premises). Data Modernization: Collaborate with cross-functional teams to assess and migrate legacy data systems to modern cloud platforms (e.g., AWS, Snowflake), optimizing for performance, cost, and scalability. Innovation: Stay ahead of emerging data technologies like Data Mesh, Data Fabric, and API-driven services, and lead their implementation within the organization. Collaboration: Partner with data engineers, data governance, and business stakeholders to understand their data needs and provide feasible data solutions.

Requirements

• Computer science, engineering, mathematics, or related field bachelor's degree or higher.
• Minimum of 10 years of experience in data architecture, data management, data engineering, data analysis, or data science roles with demonstrated success in leading and delivering complex data projects.
• Ability to design and implement data architectures that support business goals and objectives.
• Knowledge of data technologies and platforms, such as SQL, Python, Spark, Kafka, Snowflake, DBT, AWS, Azure, or GCP.
• Solid understanding of data architecture/data engineering concepts and techniques, such as data modeling, data warehousing, data integration, data pipeline, data lake, data quality, and data security.
• Experience in designing and building data solutions that use advanced analytics and machine learning.
• Outstanding communication, presentation, and leadership skills, with the ability to work with and persuade diverse stakeholders.
• Strong problem-solving, analytical, and critical thinking skills, with the ability to deal with ambiguity and complexity.
• Enthusiasm for learning and keeping up with the latest developments and innovations in data engineering.
• Knowledge of data governance frameworks, standards, policies, and best practices.
• Ability to manage and coordinate data projects across multiple teams and departments.
• Awareness of current and emerging data trends, challenges, and opportunities

Responsibilities

• Manage the data architecture team and provide technical guidance, mentorship, and feedback.
• Define and execute the data architecture roadmap and vision, in alignment with the data strategy and business objectives.
• Design and implement data solutions that leverage modern technologies, such as cloud, streaming, and machine learning.
• Establish and enforce the data architecture defined patterns, tools and technologies. This includes data sourcing, landing, transformation, and data access capabilities. In addition, working with the Enterprise Architecture team to adhere to Enterprise Architecture standards and patterns.
• Participate in troubleshooting the data environment issues and incidents and provide expertise to support root cause analysis and resolution.
• Evaluate and recommend new data tools, technologies, and frameworks, and conduct proof of concepts and pilots with the Data Engineering team.
• Communicate and present the data architecture strategies and solutions to various audiences, such as senior management, business users, and technical teams.
• Architect and Design Data Platforms: Overseeing the design and implement scalable, cloud-based data architectures, enabling real-time and batch data processing to support analytics, AI/ML, and business intelligence use cases.
• Data Integration: Lead efforts to integrate diverse data sources (structured, semi-structured, and unstructured), ensuring data consistency, quality, and availability across hybrid environments (cloud and on-premises).
• Data Modernization: Collaborate with cross-functional teams to assess and migrate legacy data systems to modern cloud platforms (e.g., AWS, Snowflake), optimizing for performance, cost, and scalability.
• Innovation: Stay ahead of emerging data technologies like Data Mesh, Data Fabric, and API-driven services, and lead their implementation within the organization.
• Collaboration: Partner with data engineers, data governance, and business stakeholders to understand their data needs and provide feasible data solutions.

Benefits

• Your wellbeing is important to Pacific Life, and we’re committed to providing you with flexible benefits that you can tailor to meet your needs. Whether you are focusing on your physical, financial, emotional, or social wellbeing, we’ve got you covered.
• Prioritization of your health and well-being including Medical, Dental, Vision, and Wellbeing Reimbursement Account that can be used on yourself or your eligible dependents
• Generous paid time off options including: Paid Time Off, Holiday Schedules, and Financial Planning Time Off
• Paid Parental Leave as well as an Adoption Assistance Program
• Competitive 401k savings plan with company match and an additional contribution regardless of participation

What This Job Offers

• Job Type: Full-time
• Career Level: Executive