Sr. Staff Data Engineer – Tech Lead – GenAI
| Company | Hartford Financial Services |
|---|---|
| Location | Chicago, IL, USA, Charlotte, NC, USA, Columbus, OH, USA, Hartford, CT, USA |
| Salary | $135040 – $202560 |
| Type | Full-Time |
| Degrees | Bachelor’s |
| Experience Level | Senior, Expert or higher |
Requirements
- Candidates must be authorized to work in the US without company sponsorship. The company will not support the STEM OPT I-983 Training Plan endorsement for this position.
- Bachelor’s degree in computer science, Data Engineering, or a related field
- Minimum 2 years of experience as a Data Engineer, with a strong track record in quantitative, analytical and data manipulation skills
- Experience with ETL tools (Informatica, IDMC etc.)
- Unit, interface and end user testing concepts and tooling (functional & non-functional)
- Knowledge on any Cloud tech stack AWS, Azure etc.
- Advanced knowledge of SQL as it pertains to data, analytics, and reporting on any relational database Oracle, SQL Server, Snowflake etc.
- Experience with any scripting or programming language – Python, JavaScript etc.
- Experience with Test automation & DevOps tools
- Knowledge of Agile Scrum/SAFE methodology
- Effectively use collaboration tools like Rally, Jira etc.
Responsibilities
- Modernize and implement the transformation roadmap for Enterprise Business Operations Billing Team using a new data reference architecture leveraging AWS cloud, Python and Snowflake. Transformation will focus on addressing challenges across legacy tech stack, data freshness issues, speed of deliver and quality.
- Integrate and aggregate complex data from multiple data sources and platforms to enhance customer access to information and promote a data-driven culture.
- Implement end-to-end generative AI pipelines, from data ingestion to pipeline deployment and monitoring.
- Develop and optimize RAG architectures and pipelines, Agentic Workflows and unstructured data processing
- Incorporate core data management competencies, including data governance, data security, and data quality.
- Develop and deploy analytical solutions leveraging machine learning technologies.
- Develop and support the migration activities of reporting assets from legacy sources to Snowflake.
- Collaborate with the Enterprise Data teams to provide user acceptance testing, maintain data quality, and advance the technical toolset.
- Develop and maintain data analytics tools and frameworks to support Artificial Intelligence & Machine Learning use cases.
- Stay up to date with emerging data technologies and industry best practices. Demonstrate a strong willingness to explore and leverage new tools and technologies as per project needs.
- Confident, self-starter capable of independently driving multiple concurrent projects to completion.
Preferred Qualifications
- Experience with any of the reporting tools –Tableau, Business Objects, Micro-Strategy
- Insurance & Financial services domain knowledge
- Knowledge of AWS cloud technology – Code Build, Code Pipeline, Containers
- Awareness of AI, ML, Data science practice