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Staff Data Engineer

The Hartford

On-site
India
Full-time
Staff
7+ yrs
Salary not listedPosted 38m ago

Real job — pulled straight from The Hartford’s careers page · Verified September 6, 2026 · No reposts.

Job description

The Hartford is hiring a Staff Data Engineer — a full-time, based in India role. Apply directly on The Hartford's careers page below.

IND Staff Data Engineer

Location: India GCC-Puppalaguda Village

Time Type: Full time

Job Description

IND Staff Engineer - GCC097

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.

  • Key Responsibilities 

    Offshore Team Leadership & People Management 

    • Lead, coach, and develop a team of offshore Data Engineers supporting enterprise Data and AI initiatives. 

    • Serve as the primary people leader for offshore team members, including performance management, career development, goal setting, and succession planning. 

    • Foster a culture of accountability, collaboration, continuous learning, and technical excellence. 

    • Support recruitment, onboarding, workforce planning, and retention strategies for offshore talent. 

    • Partner with onsite leaders to ensure team members receive appropriate mentorship, growth opportunities, and feedback. 

    Delivery Oversight & Resource Management 

    • Oversee delivery execution across a portfolio of data engineering, analytics, data product, and AI initiatives. 

    • Manage resource allocation and capacity planning to ensure alignment with organizational priorities. 

    • Monitor team utilization, delivery commitments, project risks, and operational support activities. 

    • Establish processes for work intake, prioritization, escalation management, and delivery reporting. 

    • Ensure offshore resources are effectively integrated within product-aligned and functional teams. 

    Stakeholder & Partner Management 

    • Act as the primary liaison between offshore teams and Data, Analytics, AI, and Technology leadership. 

    • Build strong partnerships with Product Managers, Engineering Managers, Architects, and Business stakeholders. 

    • Facilitate alignment of priorities, resource needs, skill development opportunities, and delivery expectations. 

    • Provide regular updates to leadership regarding team performance, capacity, delivery progress, risks, and opportunities. 

    Technical Leadership & Governance 

    • Provide technical oversight and guidance across data engineering initiatives involving Snowflake, AWS, Google Cloud Platform, data integration, analytics, and AI capabilities. 

    • Promote engineering best practices, coding standards, testing practices, CI/CD adoption, and operational excellence. 

    • Support architecture reviews and ensure solutions align with enterprise standards and strategic technology direction. 

    • Drive continuous improvement initiatives focused on reliability, scalability, security, maintainability, and cost optimization. 

    AI & Data Modernization Enablement 

    • Support adoption of emerging AI technologies, including generative AI, prompt engineering, AI-enabled automation, and agentic workflows. 

    • Partner with technical leaders to identify opportunities to improve engineering productivity, data quality, and business value through AI-enabled solutions. 

    • Encourage continuous skill development in cloud technologies, data engineering disciplines, and AI platforms. 

    • Ensure appropriate governance, controls, and validation processes for AI-enabled solutions. 

    Operational Excellence 

    • Establish and monitor key performance indicators related to delivery quality, productivity, platform stability, and team effectiveness. 

    • Drive improvements in development lifecycle processes, operational support models, and incident management practices. 

    • Ensure adherence to enterprise data governance, security, compliance, and risk management standards. 

    • Identify opportunities to improve efficiency through automation, standardization, and process optimization. 

     

    Qualifications 

    Required 

    • Bachelor's degree in Computer Science, Information Systems, Data Science, Engineering, or a related discipline. 

    • 7+ years of experience in data engineering, cloud engineering, analytics engineering, or related technology disciplines. 

    • 3+ years of leadership experience managing technical teams, preferably within a global delivery model. 

    • Experience leading offshore, distributed, or matrixed teams supporting multiple business and technology stakeholders. 

    • Strong understanding of Snowflake, SQL, ETL/ELT processes, and modern cloud-based data architectures. 

    • Experience with AWS technologies including S3, Lambda, Fargate, EC2, and related services. 

    • Understanding of Google Cloud data technologies such as BigQuery, Cloud Functions, and Vertex AI. 

    • Experience managing Agile delivery processes, resource planning, and project execution. 

    • Strong communication, stakeholder management, and organizational leadership skills. 

    Preferred 

    • Experience supporting enterprise Data & AI organizations through a Global Capability Center (GCC) or offshore delivery model. 

    • Experience managing teams supporting data products, analytics platforms, AI initiatives, and cloud modernization programs. 

    • Knowledge of ThoughtSpot, Tableau, Informatica, and modern data integration platforms. 

    • Experience implementing or supporting generative AI and intelligent automation solutions. 

    • Familiarity with enterprise governance, data management, and operating model frameworks. 

     

    Success Measures 

    • Offshore team engagement, retention, and talent development. 

    • Consistent delivery against commitments across multiple portfolio teams. 

    • Effective resource utilization and capacity management. 

    • Stakeholder satisfaction across supported Data and AI organizations. 

    • Improvement in engineering quality, operational performance, and delivery predictability. 

    • Growth in team capabilities supporting cloud, data, analytics, and AI initiatives. 

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Frequently asked questions

What skills are required for Staff Data Engineer at The Hartford?

The required skills for Staff Data Engineer at The Hartford include: Data Engineering, Snowflake, SQL, ETL, AWS, S3, Lambda, EC2, GCP, BigQuery, Agile, Tableau, Generative AI, AI.

What is the seniority level for Staff Data Engineer at The Hartford?

Staff Data Engineer at The Hartford is a Staff level position.

How do I apply for Staff Data Engineer at The Hartford?

You can view the full description and apply for Staff Data Engineer at The Hartford on EchoJobs: https://echojobs.io/job/the-hartford-ind-staff-data-engineer-djhgj.