Data Engineer

Data Engineer – GE08AE
(AI & Data Platforms)

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 Hartford seeks a driven, team-focused Data Engineer to build and support data pipelines, cloud-based data platforms, and Machine Learning Operations (MLOps) services for the Customer Operations Data Science team. The Hartford is developing industry-leading AI and machine learning capabilities to improve customer experience (CX) hin Customer Operations Data Science, we build modern AI products that optimize customer interactions across omnichannel journeys, supporting operational areas such as the Contact Center, Digital, Premium Audit, and Billing.

As a Data Engineer, you will contribute to the development of scalable data platforms and production-ready data pipelines that enable analytics, machine learning, and AI solutions. You will work closely with data scientists, machine learning engineers, product owners, and business partners to deliver reliable data assets and services that create measurable business value.

• We build AI solutions, not models.
• We are thoughtful in supporting the end-to-end business problem, with an eye toward scalable and maintainable systems.
• We are trusted and transparent.
• We collaborate closely with our business and technology partners and are mindful of their capacity to absorb change.
• We provide assets that are safe to buy.
• Our products include monitoring, observability, and governance to ensure long‑term success.
• We will earn the right to influence.
• With humble confidence, we listen carefully and become trusted partners in problem solving.
• We are practical and evolutionary.
• We first deliver a minimally viable solution and expand its sophistication over time based on customer feedback and business value.

• Design, build, and maintain scalable ETL/ELT data pipelines and integrations.
• Develop and support data ingestion, transformation, and delivery solutions using cloud‑native technologies.
• Implement data quality controls, monitoring, and observability capabilities to ensure reliable data products.
• Support machine learning and AI solutions through data engineering, feature engineering, and operationalization activities.
• Build reusable frameworks, components, and automation capabilities to increase delivery efficiency.
• Collaborate with Data Science, Enterprise Data, Cloud Enablement, Architecture, and Business teams to deliver data solutions.
• Develop and maintain CI/CD pipelines and Infrastructure as Code (IaC) assets to support cloud‑based deployments.
• Assist with the deployment, monitoring, and support of production data and AI services in AWS and GCP environments.
• Troubleshoot and resolve data pipeline, integration, and platform performance issues.
• Participate in Agile ceremonies, code reviews, technical documentation, and continuous improvement activities.
• Follow and promote software engineering, Data Ops, and MLOps best practices.

• Must be authorized to work in the U.S. now and in the future.
• Bachelor's degree in Computer Science, Data Engineering, Information Systems, or related field, or equivalent work experience.
• Experience building and supporting data pipelines in cloud‑based environments.
• Experience with SQL development and relational database concepts.
• Experience with Python or similar programming languages.
• Familiarity with AWS and/or GCP cloud services.
• Experience with source control systems such as Git Hub.
• Experience with CI/CD tools such as Git Hub Actions, Jenkins, or similar platforms.
• Experience with Infrastructure as Code (Terraform, Cloud Formation, or similar technologies).
• Familiarity with workflow orchestration tools such as Apache Airflow, Cloud Composer, or similar platforms.
• Experience working with data warehouse technologies such as Snowflake, Redshift, Big Query, or similar platforms.
• Understanding of data quality, data governance, and data lifecycle management principles.
• Familiarity with API…