Principal Data Architect
| Company | Hartford Financial Services |
|---|---|
| Location | Chicago, IL, USA, Charlotte, NC, USA, Columbus, OH, USA, Hartford, CT, USA |
| Salary | $140000 – $210000 |
| Type | Full-Time |
| Degrees | Bachelor’s, Master’s |
| Experience Level | Expert or higher |
Requirements
- Expert understanding of cloud platforms (e.g., AWS, GCP, Snowflake)
- Extensive knowledge of Informatica IDMC for data integration and transformation
- Extensive knowledge of database systems (SQL, PostgreSQL, NoSQL, vector, graph)
- Experience with Python, PySpark
- Excellent communication, presentation, and leadership skills
- Ability to influence and collaborate with senior leadership
- 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
- Bachelor’s or Master’s degree in Computer Science, Information Systems, a related field, or equivalent work experience
- 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
Responsibilities
- 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
- 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
- Drive the creation and maintenance of data domains across the enterprise
- Architect and design complex data platforms leveraging Snowflake, AWS, GCP, and other cutting-edge technologies
- 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
- Provide technical leadership and guidance on data architecture best practices, including data governance, data security, and data integration
- Architect and optimize data solutions on cloud platforms, specifically AWS and GCP, leveraging cloud-native services for scalability and reliability
- Design and implement data integration solutions using Informatica IDMC, Python, and PySpark, ensuring seamless data flow across various systems
- Design and implement data architectures that are reliable, scalable, and resilient, ensuring high availability and performance while running in a cost-optimized manner
- Design and implement architectures for streaming data applications, enabling real-time data processing and analytics
- Designing data architectures that align to and support Enterprise Data Governance framework, ensuring data quality, security, and compliance
- 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
- 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
- Continuously evaluate and recommend new data technologies and trends to improve our data capabilities
Preferred Qualifications
- Recognized applicable domain certifications (e.g., AWS Data and Analytics, GCP Professional Data Engineer, SnowPro Advanced Architect)