greenhouse
Senior Technical Product Manager
Movable Ink
Remote, CAN
Full-time
Senior · 5+ years experience
Remote
CAD 123300-160000 yearly / year
Discovered 1 weeks ago
SnowflakeKafkaDatabricksAirflow
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Responsibilities
- Own the product backlog for the event data pipeline, including stream event ingestion and tracking, normalization of data generated by ML and platform features, and governed data infrastructure, driving sprint-level execution with data engineering partners
- Translate use cases and functional requirements from Sales, CX, and other cross-functional teams into well-scoped product requirements the engineering team can execute against
- Serve as a visible and trusted partner to commercial and cross-functional teams, maintaining active presence in Sales and CX conversations and ensuring the team's work is understood and connected to customer and business needs
- Pitch in across the data and integrations portfolio where event data pipeline decisions create cross-team dependencies, contributing to a coherent platform roadmap beyond your immediate backlog
- Define and track reliability and quality benchmarks for shipped pipeline features, monitoring performance in the 60 to 90 days following go-live
- Stay current on the evolving event data and data platform landscape, bringing informed perspective to architectural trade-off conversations with engineering
- Be a ruthless advocate for our customers in every interaction and decision
Qualifications
- 5+ years of product management experience working directly with engineering teams on technically complex, data-intensive products
- Fluency in event data pipeline concepts including stream event ingestion, real-time data processing, and data normalization
- Familiarity with modern data stack technologies such as Snowflake, Kafka, Databricks, or Airflow; prior software engineering or data engineering experience is a strong plus
- Demonstrated ability to translate use cases and functional requirements from commercial or non-technical stakeholders into clear, actionable product requirements
- Comfortable building credibility with both data engineering teams and commercial partners such as Sales and CX
- Strong prioritization instincts across a defined backlog with an eye toward broader platform dependencies
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