Data Engineer focused on building and maintaining data pipelines using SQL Server and T - SQL. Designing data solutions for reporting and analytics from various internal and third - party systems.
About the role
- AVP of AI and Data Engineering for The Hartford, driving modernization of data analytics ecosystems. Overseeing large-scale data projects and strategies with leadership responsibilities.
Responsibilities
- Lead the strategy and execution of complex and large Global Specialty Data and Analytics portfolio
- Develop and implement a strategic roadmap to modernize legacy data and analytics ecosystems using Cloud and AI
- Solve for data complexity by enabling data domains and data products for all consumption architypes and stakeholders including reporting, data science, AI/ML and analytics
- Ensure data architecture and solutions align with enterprise-wide standards for Data, AI and Analytics
- Effectively communicate strategy, execution progress, and outcomes to diverse stakeholders and promote data capabilities through thought leadership and presentations
- Implementing AI data pipelines that integrate structured, semi-structured, and unstructured data to support AI and Agentic solutions
- Design, build and maintain scalable real-time data pipelines for efficient ingestion, processing, and delivery
- Oversee the design, development, and maintenance of data pipelines, data warehouses, data lakes and reporting systems
- Build, mentor, and lead a high-performing team including business data analysts, data engineers and release train engineers
- Identify and champion developer productivity improvements across the end-to-end data management lifecycle
- Stay current with emerging trends in data engineering and AI/ML and recommend innovative tools and technologies to enhance data capabilities enabling business strategy
- Define and implement robust data management frameworks to ensure successful adoption of Enterprise Data Governance and Data Quality practices
- Effectively manage the budget and financials for GS Data and Analytics portfolio
Requirements
- 15+ years in data engineering, data management and building large-scale data ecosystems
- Bachelor’s or Master’s degree in Computer Science, Data Science or a related field
- 5+ years in senior leadership roles managing large and complex data and analytics portfolio with a people budget of at least $10M
- Proven strategic and innovative thinker with a track record of enabling transformative data capabilities
- Mastery level data engineering and architecture skills, including deep expertise in data architecture patterns, data warehouse, data integration, data lakes, data domains, data products, business intelligence, and cloud technology capabilities
- Technical expertise in LLMs, AI platforms, prompt engineering, LLM optimization, Retrieval-Augmented Generation (RAG) architectures and vector database technologies (Vertex AI, Postgres, OpenSearch, Pinecone etc.)
- Strong experience with GCP, Vertex AI or AWS required
- Experience in multi cloud environment
- Experience in Lang chain, AI agents, Vertex AI and Google Agent ecosystem
- Strong experience with the design and development of complex data ecosystems leveraging next-generation cloud technology stack across AWS or GCP Cloud and Snowflake
- Exceptional presentation and verbal/written communication skills; must be able to communicate effectively at all levels across the organization
- Ability to lead successfully in a lean, agile, and fast-paced organization, leveraging Scaled Agile principles and ways of working
- Excellent negotiation, influencing, and conflict resolution skills; adept at building strong cross-functional relationships
Benefits
- Other rewards may include short-term or annual bonuses
- Long-term incentives
- On-the-spot recognition
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