Product Manager, Data Orchestration

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.

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.

• 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.

• 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.

• 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.

• 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.