Sr Cloud Data and AI Engineer

The Hartford•Hartford, CT

3h•Hybrid

About The Position

We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals – and to help others accomplish theirs, too. Join our team as we help shape the future. The Employer Group Actuarial Service area is seeking a Senior Cloud Data Engineer who combines deep expertise in cloud data engineering with a passion for Artificial Intelligence (AI), automation, and modern data platforms. The ideal candidate will help design and implement scalable data solutions while leveraging emerging AI technologies, intelligent automation, and cloud-native capabilities to accelerate business insights, operational efficiency, and innovation across Employer Benefits actuarial functions. This position is in a small group that works directly with our customers and prides itself in delivery capabilities. This role offers the opportunity to have a significant bottom-line impact through the delivery of quality and actionable information to our business customers. The ideal candidate is a highly motivated, results-oriented individual with strong technical skills and project-level leadership experience. We are looking for a well-rounded individual that is comfortable working in a process light environment and willing to cross the traditional role boundaries of developer, BA, Architect and project lead. To be successful in this role you must be comfortable working directly with customers in an iterative fashion to achieve the desired result. As such, strong verbal communication and the ability to create your own technical specifications and designs based on customer needs is critical for success in this role. This role can have a Hybrid or Remote work schedule. Candidates who live near one of our 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 should maintain their current work arrangement with the expectation of coming into the office as business needs arise.

Requirements

Bachelor’s degree with at least 7 years of applicable work experience.
Experience in following is required: Snowflake, IDMC, Informatica, Oracle
Hands-on experience using AI-assisted engineering tools, Snowflake Cortex and Agentic AI capabilities, Generative AI platforms, Model Context Protocol (MCP), cloud-based AI services, and intelligent automation frameworks.
Experience building AI-powered self-service analytics, intelligent data catalogs, automated reconciliation frameworks, or knowledge management solutions.
Demonstrated passion for continuous learning in Artificial Intelligence, cloud architecture, automation, and emerging technologies.
Experience with CICD, GitHub, Autosys, and SQL
7+ years ETL / Data analysis / Warehouse Technologies experience
Strong data warehouse knowledge preferably in the insurance domain,
Demonstrated expertise in Data analysis, Data Quality and reconciliation processes.
Strong experience in Python , R and other modern languages, including experience building APIs, automation frameworks, AI-driven applications, and cloud-native data services.
Experience in on-premises to cloud migration of data pipelines, modernizing them to leverage full cloud potential.
Experienced in Agile and Kanban Methodologies
Candidate 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.

Nice To Haves

Group Benefits business knowledge is a plus.
Knowledge of AWS and cloud-based data solutions is a plus

Responsibilities

Regularly engage in continuing education and serve as a technical expert in Informatica IDMC, Snowflake, AI and Generative AI platforms, cloud-native data services, CICD tooling, environment management, Oracle, metadata-driven architectures, and enterprise data quality processes.
Evaluate, prototype, and operationalize emerging AI technologies, including Generative AI, Agentic AI workflows, Retrieval Augmented Generation (RAG), and Model Context Protocol (MCP)-based integrations.
Design and develop high quality, scalable data solutions to enable pricing and reserving activities for Employer Benefit Actuarial team.
Ability to synthesize, reconcile, and explain data differences between GB actuarial output against other standard published data.
Gain deep understanding on various Actuarial applications, data elements and business process.
Work closely with Actuarial customers during the close of current financial months to provide solutions to time sensitive issues while ensuring strategic solutions are planned for next release cycle.
Provide technical leadership and mentorship to junior engineers while fostering collaboration across onshore and offshore teams to deliver innovative, scalable, and sustainable data solutions.
Leverage strong analytical and problem-solving skills to discover, integrate, and optimize data from diverse sources, enabling informed decision-making and supporting mission-critical business processes.
Ability to discover, analyze and integrate data from various sources to support decision making and enable critical business processes
Consult with cross-functional team partners to understand business needs and develop reliable and effective solutions that are easily maintainable.
Ability to work directly with the customers to understand their needs and provide solutions.
Willingness to develop deep functional knowledge in the pricing and rating process.
Develop and maintain scalable data pipelines and ETL processes to support Insurance processing, actuarial analysis, and reporting.
Use Enterprise GitHub for version control, documentation, code collaboration, and technical project management.
Research, evaluate, and champion modern data technologies, frameworks, and best practices to drive operational excellence and accelerate data-driven innovation.
Build deep functional knowledge of pricing, rating, and actuarial processes while working within agile delivery frameworks and partnering across organizations to enhance enterprise data assets and capabilities.