Sr Data Engineer
- Category: MIS Executive
- Location: Gurugram, Haryana
- Job Type: Full Time / Part Time
- Salary: Estimated: $ 17K to 34K
- Published on: 2025/09/21
The Senior Data Engineer role is a strategic partner within the People Analytics Data Engineering team responsible for the design, development, automation, and integration of HR data assets to prepare our business for the future of work. We're looking for someone with at least 6+ years of experience in designing solutions, owning platforms, and drawing insights from data, and someone with at least 4 years of experience managing data pipeline and integration projects.
Manage People Analytics Data Assets
• Catalog current data integration and automation processes and recommend best practice methods for improvement and optimization.
• Partner with the head of People Analytics Data Engineering to create roadmaps and execute project plans in fast-paced agile development environment.
• Research and recommend technologies and processes to support rapid scale and future state growth initiatives.
• Prioritize business needs, leadership questions, and ad-hoc requests for on-time delivery.
• Manage team JIRA boards and Data Pipeline metrics to support team operations, leadership reporting, and continuous improvement initiatives.
Lead Data Engineering Implementation Projects
• Design dimensional data models to support business requirements and people analytics data warehouse optimization.
• Build complex data pipelines for our highest priority projects.
• Serve as a release manager reviewing junior data and analytics engineers' work products for bugs, efficiently, and scale to enable production deployments.
• Partner with our Human Resources Information Technology (HRIT) team to complete architecture review exercises and gain approval from data security and privacy teams.
Support HR Analytics and Reporting Strategy
• Support the future state of HR Analytics at Gartner, including the execution of our multi-year roadmap.
• Lead QA and Development efforts for automation, data pipelining, and dashboarding within the team.
• Support projects that improve our performance (e.g. Quality of Hire): requirements, discussions, problem solving, analytics, share insights, build solutions, drive change
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