Data Engineer - GE08AE
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.
Join The Hartford's Enterprise Data Services organization and help build the next generation of metadata-driven and agentic data solutions. As a Data Engineer, you'll work with cutting-edge cloud technologies, modern engineering practices, and AI-assisted development tools to deliver innovative capabilities that advance data governance, automation, and intelligent workflows across the enterprise.
You'll be part of a highly collaborative team focused on transforming how data is discovered, governed, managed, and leveraged to drive business value. This is an opportunity to influence the future of enterprise data platforms while expanding your expertise in cloud engineering, metadata management, governance, and AI-enabled development.
This role will have a Hybrid work schedule, with the expectation of working in an office (Columbus, OH, Chicago, IL, Hartford, CT or Charlotte, NC) 3 days a week (Tuesday through Thursday).
What's in it for you?
Design and build enterprise-scale data engineering solutions that power metadata-driven and intelligent automation capabilities.
Work hands-on with modern cloud technologies including Google Cloud Platform (BigQuery, GCS, Composer, Dataplex, APIs, and more).
Help shape the future of Data Governance through engineering-led automation, lineage services, metadata synchronization, and intelligent workflows.
Collaborate with Data Governance, Product, Platform Engineering, and business partners to deliver innovative enterprise capabilities.
Leverage AI-assisted development tools such as GitHub Copilot and other modern engineering accelerators to increase productivity and innovation.
Build reusable frameworks, APIs, and platform services that accelerate adoption and standardization across the enterprise.
Drive engineering excellence through CI/CD, automation, testing, observability, DataOps, and DevSecOps practices.
Influence and support the development of agentic and AI-enabled solutions that improve business processes and governance outcomes.
Expand your expertise in cloud data architecture, security, governance-by-design, and scalable data engineering patterns.
Work in a supportive, forward-thinking environment that values innovation, continuous learning, collaboration, and career growth.
What you'll do
- Build scalable, production-ready data pipelines and orchestration workflows on GCP.
- Develop integrations between enterprise data platforms and governance systems to enable metadata discovery, lineage, and automation.
- Design and deploy secure, reliable, observable, and cost-efficient cloud-based data solutions.
- Embed governance controls directly into engineering workflows through metadata capture, classification, policy enforcement, and lineage propagation.
- Contribute to the development of intelligent automation solutions that leverage governed metadata and business context.
- Partner with stakeholders to deliver reusable, high-quality engineering solutions aligned with enterprise architecture standards.
- Improve operational excellence through automation, monitoring, testing, CI/CD, and platform engineering best practices.
- Required Qualifications: Strong hands-on experience with Google Cloud Platform, including BigQuery, Cloud Storage, IAM, and orchestration technologies.
- Proficiency in Python and SQL for data engineering, automation, API development, and scalable data processing.
- Experience building and supporting enterprise data pipelines, ETL/ELT processes, or data services.
- Understanding of software engineering best practices including source control, testing, CI/CD, and modular application design.
- Experience designing and implementing secure, production-grade cloud solutions.
- Familiarity with AI-assisted software development tools and the ability to effectively evaluate and apply AI-generated solutions.
- Excellent problem-solving, collaboration, and communication skills.
Preferred Qualifications:
- Bachelor's degree in Computer Science, Engineering, Information Technology, Data Analytics, or a related field, or equivalent professional experience.
- Experience with AI, agentic solutions, intelligent automation, or machine learning-enabled workflows.
- Familiarity with metadata-driven architectures and data catalog technologies.
- Experience with data governance platforms such as Informatica IDMC/CDGC, Dataplex/Knowledge Catalog, Collibra, or similar solutions.
- Knowledge of data lineage, data quality, metadata management, and business glossary concepts.
- Experience with API integration, event-driven architectures, and API security practices.
- Exposure to Snowflake, multi-cloud architectures, Terraform, or Infrastructure-as-Code practices.
- 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.
