Full Stack Engineer, Data Orchestration

Posted Yesterday
27 Locations
Remote
Mid level
Machine Learning • Software • Database
The Role
Build end-to-end features for a data orchestration platform across Java/Micronaut backend and Vue 3/TypeScript frontend. Implement data-aware orchestration (assets, lineage, freshness, quality), create integrations/plugins (dbt, Fivetran, Airbyte, warehouses), improve UI (flow editor, topology, dashboards), collaborate on 8-week releases, review PRs, and engage with the open-source community.
Summary Generated by Built In
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 Full Stack Engineer to build the features data teams use to orchestrate their pipelines with Kestra: data-aware orchestration, integrations with tools like dbt, Fivetran, Airbyte, Snowflake, BigQuery, and Databricks, and the UI where pipelines are built, run, and monitored. Hands-on data engineering experience is a must: you'll build for data engineers and analytics engineers, and you need to understand their workflows from your own practice. You'll work across our whole stack, from the Java/Micronaut backend to the Vue 3 + TypeScript frontend, and release features in 8-week cycles with minimal process.

What You'll Do
  • Build features end to end - from the Java Micronaut backend (REST APIs, orchestration engine, plugins) to the Vue 3 frontend, including tests and documentation.

  • Develop data-aware orchestration - assets, lineage, freshness, and data quality as part of the orchestration model.

  • Build and improve plugins - integrations with dbt, Fivetran, Airbyte, cloud warehouses, and other tools of the modern data stack.

  • Work on the UI data teams use daily - the flow editor (Monaco), topology views, dashboards, and execution monitoring.

  • Collaborate with the Product Manager and other engineers to scope and deliver features for each 8-week release cycle.

  • Review pull requests, discuss changes publicly on GitHub, and engage with the open-source community.

What We're Looking For
  • Hands-on data engineering experience - you've built or operated data pipelines yourself, with tools like dbt, Fivetran or Airbyte, warehouses such as Snowflake, BigQuery, or Databricks, or an orchestrator such as Airflow, Dagster, or Prefect.

  • Strong experience with Java and a modern backend framework - we use Micronaut, and experience with Spring Boot or Quarkus is a good fit.

  • Solid frontend skills with Vue 3 and TypeScript - we also use Pinia, Vite, and the Monaco editor. Deep experience with React or another modern framework can work if you're willing to go deep on Vue.

  • Good knowledge of SQL and relational databases - PostgreSQL, MySQL, and H2 are supported as Kestra backends.

  • Understanding of distributed systems: queues, schedulers, and workers processing jobs reliably at scale.

  • Comfortable with Docker and CI/CD pipelines.

  • Excellent communication and clarity in writing - comfortable discussing technical decisions publicly in GitHub repositories.

  • Full ownership mentality. You iterate quickly based on feedback and don't wait to be told what to do.

  • Comfortable working with globally distributed teams across time zones.

Bonus Points
  • Past experience working as a data engineer or analytics engineer, beyond building pipelines as a side task.

  • Experience with Kafka or Elasticsearch (both are part of the Kestra Enterprise Edition backend).

  • Experience with Kubernetes and cloud infrastructure (AWS, GCP, or Azure).

  • Contributions to open-source projects.

  • Experience in a B2B software or open-source company.

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.

Skills Required

  • Hands-on data engineering experience (building/operating data pipelines)
  • Strong experience with Java and a modern backend framework (Micronaut, Spring Boot, Quarkus)
  • Solid frontend skills with Vue 3 and TypeScript
  • Proficiency with SQL and relational databases (PostgreSQL, MySQL, H2)
  • Understanding of distributed systems: queues, schedulers, workers
  • Familiarity with Docker and CI/CD pipelines
  • Excellent written communication and ability to discuss technical decisions publicly
  • Experience with modern data stack tools (dbt, Fivetran, Airbyte) and cloud warehouses (Snowflake, BigQuery, Databricks)
  • Experience with orchestration tools (Airflow, Dagster, Prefect)
  • Experience with Vue ecosystem tools (Pinia, Vite) and Monaco editor
  • Experience with Kafka, Elasticsearch, Kubernetes, or cloud infra (AWS/GCP/Azure)
  • Open-source contributions or experience at a B2B/open-source company
Am I A Good Fit?
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The Company
Paris
35 Employees
Year Founded: 2022

What We Do

Kestra is an open-source orchestration platform that makes both scheduled and event-driven workflows easy. By bringing Infrastructure as Code best practices to data, process, and microservice orchestration, you can build reliable workflows and manage them with confidence. In just a few lines of code, you can create a flow directly from the UI. Thanks to the declarative YAML interface for defining orchestration logic, business stakeholders can participate in the workflow creation process. Kestra offers a versatile set of language-agnostic developer tools while simultaneously providing an intuitive user interface tailored for business professionals. The YAML definition gets automatically adjusted any time you make changes to a workflow from the UI or via an API call. Therefore, the orchestration logic is always managed declaratively in code, even if some workflow components are modified in other ways (UI, CI/CD, Terraform, API calls).

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