Senior Product Manager - Data Integrations
New
J
JobgetherDevOps analytics
Must be based in Bangalore, India, or willing to relocate, with availability to attend the Bangalore office when required for business or team activities.Full-TimeSenior
Salary not disclosed
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Job Details
- Required Skills
- ETLProduct ManagementDevOpsData modeling
Requirements
- Demonstrated product management experience translating customer needs into product priorities and strategic decisions.
- Strong understanding of the DevOps ecosystem and software development workflows, including planning, security, observability, and IT service management.
- Working knowledge of data integration concepts, including ETL, data transformation, and mapping multiple sources into common data models.
- Experience collaborating with engineering teams to define technical requirements, manage product backlogs, and deliver complex product capabilities.
- Familiarity with AI-powered tools and coding agents for prototyping, exploration, and documentation.
- Experience defining product metrics, evaluating adoption, and using data to guide decisions.
- Ability to prioritize and make product decisions with incomplete information and evolving requirements.
- Ability to work independently in distributed, remote-first teams across multiple time zones.
- Strong written communication and documentation skills for asynchronous collaboration.
- Experience with data integration products, data modeling, analytics platforms, or value stream analytics is advantageous but not required.
Responsibilities
- Define and drive the strategy and roadmap for data integrations based on customer needs, market opportunities, and business priorities.
- Gather customer, field-team, and product-stakeholder insights to identify integration gaps and prioritize opportunities.
- Shape how external data sources integrate into shared data models, including ETL processes and data transformation strategies.
- Define customer problems, target users, use cases, and expected outcomes for each integration.
- Collaborate with engineering teams on product requirements, technical trade-offs, user experiences, and delivery timelines.
- Translate product strategy into epics, issues, and development backlogs.
- Define telemetry, adoption metrics, and success indicators; use product usage and customer feedback to refine priorities.
- Contribute to pricing and packaging strategies as the data integration offering evolves.
- Use AI coding agents and product development tools to explore datasets, prototype integrations, and document product experiences.
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