Director, Data Architect

Jobtailor; Connecticut; On-site; USD 180,000 - 240,000; Full time

Job summary

Jobtailor in Connecticut is seeking a senior Data & Analytics leader to drive strategy and execution for a large data portfolio.

You will modernize legacy ecosystems using Cloud and AI, ensure alignment with enterprise standards, and design scalable real-time pipelines and lakehouse architectures.

Lead a diverse team of directors, data engineers, and analysts, champion productivity, and communicate clearly across all levels of the organization to deliver business insights and AI-enabled solutions.

Qualifications

• 12+ years in data engineering and large-scale data ecosystems.
• 7+ years in leadership managing large data/analytics teams.
• Strategic thinker with a track record enabling data capabilities.
• Expertise in data architecture, lakehouses, data integration and cloud tech.

Responsibilities

• Lead strategy and execution of a complex Data & Analytics portfolio.
• Develop and implement a roadmap to modernize data ecosystems with Cloud/AI.
• Ensure data architecture aligns with enterprise standards for Data/AI/Analytics.
• Lead AI data engineering to support AI and Agentic solutions.
• Design and maintain scalable real-time data pipelines.
• Oversee lakehouse architectures, data warehouses/lakes, and reporting systems.
• Mentor Directors, Data Engineers, and analysts; improve developer productivity.
• Champion end-to-end data management lifecycle improvements.

Skills

Data Integration

Lakehouse Architecture

Data Warehousing

Data Lakes

Conversational BI

LLM Optimization

Prompt Engineering

RAG Architectures

Education

Bachelor's or Master's in CS / Data Science

Tools

Vertex AI

Postgres

OpenSearch

Pinecone

Snowflake

GCP

AWS

Job description

Responsibilities

• Lead the strategy and execution of complex and large Data and Analytics portfolio.
• Develop and implement a strategic roadmap to modernize legacy data and analytics ecosystems using Cloud and AI.
• Ensure data architecture and solutions align with enterprise-wide standards for Data, AI and Analytics.
• AI Data Engineering leader responsible for 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 lakehouse architectures, data pipelines, data warehouses, data lakes and reporting systems.
• Mentor and lead a high‑performing team including Directors, Business data analysts, Data engineers and Release train engineers.
• Identify and champion developer productivity improvements across the end‑to‑end data management lifecycle.

Requirements

• 12+ 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.
• 7+ years in leadership roles managing large and complex data and analytics portfolio with large size teams.
• 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, lakehouses, data integration, data domains, data products, conversational 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.
• 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.
• Preferred experience in the Employee Benefit insurance industry.

Hard Skills

• Data Integration
• Lakehouse Architecture
• Data Warehousing
• Data Lakes
• Conversational Business Intelligence
• LLM Optimization
• Prompt Engineering
• Retrieval‑Augmented Generation
• Data Products
• Data Domains

Soft Skills

• Exceptional Communication Skills
• Strategic Thinking
• Innovative Problem Solving
• Mentoring