Director AI Data Architecture

t data platforms. This will be a hands on architect role.

This role can have a Hybrid or Remote work schedule. Candidates who live near one of our office 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 will have a remote work arrangement, with the expectation of coming into an office as business needs arise. Candidates must be authorized to work in the US without company sponsorship.

Primary Job Responsibilities

• Strategic Data Architecture Leadership: Develop and maintain line of business data architecture, aligned to Enterprise data architecture and strategy, including data models, data pipelines, data warehouses, data lakes, and data marts.

• GenAI Data Architecture: Design and implement data architectures to support GenAI applications, including data ingestion, storage, processing, and retrieval for large language models (LLMs) and other AI/ML models.

• Implementation and Delivery: Drive the creation and maintenance of scalable data domains and data products that align with enterprise standards and data strategy.

• Advanced Data Platform Design: Architect and design complex data platforms leveraging Snowflake, AWS, GCP, and other cutting-edge technologies.

• Technology Evaluation and Adoption: Partner with Architecture, Data Science, and Engineering Leadership to evaluate and recommend new data technologies and trends, including those related to GenAI, to enhance our data capabilities and drive innovation.

• Technology Leadership: Provide technical leadership and guidance on data architecture best practices, including data governance, data security, and data integration.

• Cloud-Native Architecture: Architect and optimize data solutions on cloud platforms, specifically AWS and GCP, leveraging cloud-native services for scalability and reliability.

• Data Integration and Transformation: Construct high-level design and implement data integration solutions using Informatica IDMC, Python, and PySpark, ensuring seamless data flow across various systems.

• Reliability and Optimization: Design and implement data architectures that are reliable, scalable, and resilient, ensuring high availability and performance while running in a cost-optimized manner.

• Streaming Data Applications: Design and implement architectures for streaming data applications, enabling real-time data processing and analytics.

• Data Governance and Security: Designing data architectures that align to and support Enterprise Data Governance framework, ensuring data quality, security, and compliance.

• Mentorship and Evangelism: Mentor junior team members, actively lead Communities of Practice, and author/co-author and evangelize standards and best practices that promote construction of high-quality data products and AI solutions.

• Documentation: Accountable for the creation and maintenance of comprehensive documentation of data architecture designs, standards, and best practices, as well as ensuring broad awareness of such documentation.

• Stay Current: Continuously evaluate and recommend new data technologies and trends to improve our data capabilities.

Skills

• Expert understanding of cloud platforms (e.g., AWS, GCP, Snowflake).

• 10+ years of experience in data architecture, with a focus on enterprise-level data solutions.

• Deep expertise in designing and implementing data architectures for GenAI applications.

• Proficiency in designing and implementing scalable agentic workflows for AI systems. (AWS (Lambda, S3, EC2, SageMaker) , Langchain, Langgraph etc. or GCP Vertex AI , embedding, chunking and grounding strategies)

• Experience with Python, PySpark.

• Excellent communication, presentation, and leadership skills.

• Ability to influence and collaborate with senior leadership.

• Strong knowledge of vector databases, graph databases, NoSQL, Document DBs , including design, implementation, and optimization. (e.g. AWS open search or GCP Vertex AI, neo4j etc. Mongo, Dynamo etc.)

• Experience with advanced ML/AI data pipelines.

• Deep understanding of data engineering principles and best practices using cloud technologies, data pipelines, enterprise data warehousing, and large-scale data transformations.

• Ownership mentality, taking accountability for project success and the continuous improvement of data engineering processes, architecture, and operating models.

Education, Experience, Certifications and Licenses

• Knowledge of Informatica IDMC for data integration and transformation.

• Bachelor's or Master's degree in Computer Science, Information Systems, a related field, or equivalent work experience.

• 5+ years of experience of people leadership (formal or matrix).

• Preferred: Recognized applicable domain certifications (e.g., AWS Data and Analytics, GCP Professional Data Engineer, SnowPro Advanced Architect)

• Knowledge of Informatica IDMC for data integration and transformation.

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:

$140,000 - $210,000

Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age

About Us | Culture & Employee Insights | Diversity, Equity and Inclusion | Benefits