Product Manager, Data Orchestration

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