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Dir Data Architecture - GT06AE

We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals – and to help others accomplish theirs, too. Join our team as we help shape the future.

The Hartford's Enterprise Data Services (EDS) is seeking a Director of Cloud Data Architecture responsible for modernizing and simplifying Customer Data Ecosystem portfolio of assets. Customer Data Ecosystem is an Enterprise asset supporting Personal lines, Small Commercial, Middle and Large Commercial, Group Benefits, Claims and Global Specialty lines of business. It focuses on enabling 360-degree view of customers including customer profile, customer interactions and omni-channel customer insights aligned with The Hartford’s strategy.

This role can have a Hybrid or Remote work arrangement. Candidates who live near one of our locations will have the expectation of working in an office 3 days a week (Tuesday through Thursday). Candidates who do not live near an office should maintain their current work arrangement with the expectation of coming into the office as business needs arise.

Responsibilities:

Data Architecture Strategy:

• This is a very much a HANDS-ON Technical leadership role.

• As a leader, you’ll be responsible for designing and delivering the Data strategy for all consumption architypes such as data for Digital, Predictive, Prescriptive, Descriptive and Customer Data Ecosystem portfolio of assets.

• You’ll collaborate directly with senior stakeholders across various functional areas.

Current and Target State Architectures:

• Develop and maintain both current and target state data architectures.

• Define strategy and roadmaps to guide transformation efforts.

• You will be responsible for defining the vision, strategy, and roadmap for modernizing our data platforms and processes to simplify, improve efficiency, scalability and agility.

Advancing Customer Data Ecosystem:

• Create multiyear data transformation roadmap to advance customer profile and customer interaction domains enabling 360-degree view of customers. Data products advancing omni-channel customer insights including integration with operational systems.

Architecture Patterns:

• Create architecture patterns for Cloud Data ecosystems (including AWS Cloud, PySpark, Snowflake, Tableau and ThoughtSpot).

• Ensure alignment with data architecture principles, standards, strategies, and target states.

• Consider data consumption patterns across the entire ecosystem.

Industry Trends and Implications:

• Analyze emerging business and technology trends (such as Gen AI).

• Solution data platforms to enable AI.

• Knowledge or Experience building knowledge base for RAG.

• Translate these trends into actionable capabilities within functional and technology domains.

Data Governance

• Experience in solutioning for data governance, Data Quality, Lineage, Data Catalogue capture etc. holistically, strategically, dynamically on a large scale data platform.

Real-Time Data Integration:

• Design architecture patterns using near real-time or real-time data cache for integration with operational systems.

Governance and Best Practices:

• Define and enforce data architecture standards, procedures, metrics, and policies.

• Be a thought leader, driving positive change and simplification while improving delivery speed.

Large-Scale Data Ecosystems:

• Architect and design large-scale Data Ecosystems, leveraging modern data and analytical tools.

• Leverage concepts like Data Domains and Data Products.

Leadership and Collaboration:

• Lead initiatives for continuous improvement, ensuring alignment between business strategies and technology roadmaps.

• Provide technical leadership, mentoring, and coaching to technical teams.

• Collaborate with extended architecture, business, and IT support teams to develop functional and technical blueprints.

Automation and Scalability:

• Ensure that automation and data strategy implementations are scalable, reusable, and integrated.

Qualifications:

• Bachelor’s degree in management information systems, Finance, Statistics, Computer Science, or another related field.

• 15+ years of experience in Architecture, design and data engineering development of large-scale data ecosystems and delivery experience.

• 7+ years of technical leadership

• Mastery level Data Architecture skills – a deep understanding of data architecture patterns data warehouse, integration, data lake, data domains, data products, BI and cloud technology capabilities

• HANDS ON expertise in: Dynamo DB (No SQL dbs), Kinesis, AWS EC2, Python, Spark Scala Spark streaming experience is a MUST.

• Strong experience with design and development of complex data ecosystems leveraging next generation of cloud technology stack across AWS Cloud, PySpark and Snowflake.

• Strong experience on near real time data processes and handling ELT/data transformation on streaming data.

• Ingesting and curating huge volumes of data from various platforms for Digital needs (APIs), Reporting, Analytics, Transactional (operating data store and APIs) needs

• Extensive experience on No SQL databases design and optimizations for API consumptions.

• Think outside the box to create re-usable frameworks to perform complex transformations, data quality, profiling, that are metadata driven.

• Enable frameworks to automate validations and testing.

• Performance tuning and problem-solving skill is a MUST.

• Broad knowledge across multiple technologies including bid data-based solutions, micro services, container, cloud-based solutions and integration methodologies.

• Strong experience with BI tools like Tableau, ThoughtSpot or similar

• In depth knowledge of Data management strategies, principles and practices including experience with framework for data quality, data governance, data domains, data products, stewardship, and metadata management.

• Monitoring performance and advising any necessary infrastructure changes.

• Experience in the Omni Channel Customer insights and Property & Casualty insurance industry is preferred.

• Understanding of enterprise data models and utilization of transactional and relational data from sources systems like Contact Center

• Agile experience/mindset. portfolio delivery experience, engaging in the full lifecycle experience, from planning to delivery and management of the solution lifecycle to produce solution designs that are viable and can be successfully constructed, implemented, operated, and managed.

• Must be authorized to work in the U.S. without company sponsorship

Compensation

The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford’s total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is:

$138,080 - $207,120

Equal Opportunity Employer/Females/Minorities/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age

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Human achievement is at the heart of what we do.

We believe that with the right encouragement and support, people are capable of achieving amazing things.

We put our belief into action by ensuring individuals and businesses are well protected, and by going even further – making an impact in ways that go beyond an insurance policy.

Nearly 19,000 employees use their unique talents in careers that span a variety of disciplines – from developing the latest technology to creating and promoting our products to evaluating future financial risks.

We’re also committed to programs that drive education and support volunteerism, which put human beings first. We do it because it’s the right thing to do, and because when our customers, communities and employees succeed, we all do.

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