IND Staff Data Engineer
The Hartford Hyderabad, Telangana, India
Financial Services · 10,001+ employees
About the role
Lead and develop an offshore team of data engineers while overseeing the delivery of data, analytics, and AI initiatives. Act as a primary liaison between offshore teams and global leadership to ensure alignment on priorities, technical standards, and operational excellence.
What they look for
Requirements
Requires a bachelor's degree in a technical field and at least 7 years of experience in data or cloud engineering. Candidates must have 3+ years of leadership experience managing technical teams, preferably within a global delivery model.
Full 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.
About Us | Our Culture | What It’s Like to Work Here
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