About the role
About Kestra
Kestra is the universal orchestration platform: open source, declarative, and designed to orchestrate data pipelines, IT automation, business workflows, and AI/agentic systems.
Trusted by over 10,000 organizations worldwide, including JPMorgan Chase, Bloomberg, FILA, and Crédit Agricole, Kestra orchestrates mission-critical workloads at scale. The open-source project has close to 30,000 GitHub stars, hundreds of contributors, and a fast-growing global community.
The Role
We're looking for a pragmatic Product Manager to lead Kestra's product in the data orchestration domain: how data teams build, run, and monitor pipelines with Kestra, from ingestion and transformation to data-aware orchestration across the tools they already use. You'll take features from customer problem to delivery with minimal process. This is not a "project manager" or "product owner" role; we care about releasing real value fast and won't ask you to maintain SCRUM rituals.
What You'll Do
Own the full product lifecycle - understand the problems of data engineers, analytics engineers, and data platform teams; define technical specs; prototype (AI tools encouraged); and work closely with developers to deliver high-quality releases.
Shape Kestra's data-aware orchestration - pipelines modeled around the datasets they produce, with lineage, freshness, and data quality treated as part of orchestration.
Deepen integrations with the modern data stack - dbt, Fivetran, Airbyte, Snowflake, BigQuery, Databricks, Kafka, and the wider Kestra plugin ecosystem.
Make migrations easy - clear paths and documentation for teams moving to Kestra from Airflow and similar orchestrators.
Collaborate with the Product Lead and CTO to shape and scope features for each 8-week release cycle.
Make informed tradeoffs, balancing simplicity, technical feasibility, and long-term sustainability.
Coordinate development progress and ensure features are delivered, QA'd, documented, and ready to go.
Improve the product continuously based on customer feedback, usage data, and community input.
What We're Looking For
Hands-on, startup-minded PM comfortable working without heavy process or structure.
Strong background in the data domain - you've built or managed data pipelines yourself and know tools like dbt, Fivetran or Airbyte, and warehouses such as Snowflake, BigQuery, or Databricks from hands-on use.
Practical experience with workflow orchestration (Airflow, Dagster, Prefect, or Kestra itself) and a clear understanding of scheduling, backfills, retries, and dependencies between datasets.
Excellent communication and clarity in writing - specs, product decisions, and public-facing documentation.
Full ownership mentality. You iterate quickly based on feedback and don't wait to be told what to do.
Experience or familiarity with open-source development - comfortable writing publicly and discussing product changes in GitHub repositories.
Comfortable working with globally distributed teams across time zones.
Bonus Points
Past experience as a data engineer or analytics engineer.
Experience moving a team from Airflow (or another orchestrator) to a new platform.
Experience in a B2B software or open-source company.
Exposure to SaaS products, especially self-serve or platform-oriented.
Familiarity with data engineering communities and how they adopt tools.
What You Get
Real ownership in a globally distributed, technical team.
Direct exposure to product strategy and company priorities.
A product running mission-critical workloads in production at over 10,000 organizations.
Competitive compensation, equity, and health insurance.
Originally posted on Himalayas