The Hartford
GCP Data Engineer
United States · Hybrid · Full time
Apply on the employer’s site ↗See how well you match this job
You apply directly with the employer. ROLIVA does not submit applications from this page and is not the employer.
About the role
Description from the employer’s posting. Check the employer’s page for the current version.
- EmployerThe Hartford
- LocationUnited States
- Work styleHybrid
- Employment typeFull time
- Employer posted
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.
Show full description
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.
Compensation
The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford’s total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is:
$100,960 - $151,440
Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age
About Us | Our Culture | What It’s Like to Work Here | Perks & Benefits
Check your resume against this job Free, no sign-up. Nothing you paste is stored.
Staying safe while you apply
- Never pay to apply, interview or accept an offer. ROLIVA never asks you for payment to apply to a job.
- Apply only through the official “Apply on the employer’s site” button, on the employer’s own site, and check that a recruiter’s email uses that employer’s own domain rather than a free email address.
- Be cautious of an offer made with no real interview, or pressure to decide quickly or share financial details early.
Does something look wrong with this listing? Use “Report broken link” in the role details, or read ROLIVA’s full job-safety guidance ↗.
Preparing for this role with ROLIVA
- Check the fit.
Compare the requirements with the experience you have confirmed, including gaps.
- Prepare honestly.
Build interview stories and application drafts from your own evidence.
- Keep track.
Save the role and record your own application status and follow-ups.
Data engineer jobs in United States
ROLIVA currently lists 229 open roles like this in United States.
Employers hiring for this
- Capital One Financial46 open roles
- Guidehouse8 open roles
- The Hartford7 open roles
- General Motors6 open roles
- ICF6 open roles
Top skills asked for
Listings whose description mentions each term. A mention is not a requirement.
Advertised salary for this role here
These are advertised ranges, not what people are paid.
- USD a year, after annualising72,000–360,000 (17 listings, 14 employers)
At a glance
- Work styleHybrid
- Employment typeFull time
- Employer posted
- Added to ROLIVA
- Last checked
Skills in this posting
Skills ROLIVA found in the employer’s own description above. A mention is not a requirement.
SQL Python Snowflake BigQuery GCP Terraform Machine learning