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Dagster Jobs (NOW HIRING)

Senior Data Engineer

San Francisco, CA

$124K - $169K/yr

Expert knowledge of SQL, and popular data engineering tools such as snowflake, dbt, Dagster etc * Experience working with DS team * A humble collaborative can-do attitude and natural curiosity

Data Engineer

$117K - $140K/yr

Build and operate robust data pipelines for ingestion, cleaning, and transformation using Databricks, Airflow, or Dagster. * Develop efficient ETL/ELT workflows in Python and SQL to support both ...

Data Platform Engineer

New York, NY · On-site +1

$125K - $150K/yr

Make Dagster and related orchestration infrastructure reliable, observable, and ergonomic for a large base of data scientists, analytics engineers, and adjacent technical users. * Expand and secure ...

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Dagster information

What is a Dagster developer?

A Dagster developer is a software engineer or data engineer who specializes in working with Dagster, an open-source data orchestrator for machine learning, analytics, and ETL. They design, build, and manage data pipelines, ensuring the reliable movement and transformation of data across systems. Dagster developers use Dagster's abstractions—such as solids, pipelines, and schedules—to orchestrate complex workflows, monitor data health, and enable reproducible data processes. Their work helps organizations gain insights and make data-driven decisions by providing robust and maintainable data infrastructure.

What is a Dagster job?

A Dagster job is a collection of operations (or ops) that define a data pipeline within the Dagster orchestration framework. Jobs specify how computations should be executed, including dependencies between operations and execution configurations. They allow users to manage data workflows reliably by enabling scheduling, monitoring, and error handling.

What is the difference between Dagster vs Data Engineer?

AspectDagsterData Engineer
Primary RoleWorkflow orchestration and data pipeline managementDesign, build, and maintain data infrastructure and pipelines
Required SkillsPython, orchestration tools, data pipeline conceptsSQL, Python, cloud platforms, ETL processes
Work EnvironmentData teams, DevOps, data platformsData teams, software engineering, cloud environments
CertificationsNone specific, familiarity with data toolsData engineering certifications (e.g., Google Cloud, AWS)

While Dagster focuses on orchestrating and managing data workflows, Data Engineers are responsible for building and maintaining the entire data infrastructure. Both roles require Python and data pipeline knowledge, but Data Engineers often have broader skills in database management and cloud platforms. Understanding these differences helps organizations assign the right responsibilities and professionals for their data projects.

What are the key skills and qualifications needed to thrive as a Dagster Data Engineer, and why are they important?

To excel as a Dagster Data Engineer, you need strong programming skills (especially in Python), experience with data pipeline design, and a background in data engineering or computer science. Familiarity with Dagster itself, orchestration tools, cloud platforms (such as AWS or GCP), and containerization technologies like Docker is highly beneficial. Problem-solving ability, attention to detail, and effective communication are essential soft skills for collaborating with teams and debugging complex workflows. These competencies ensure the reliable, scalable, and efficient delivery of data products within modern data ecosystems.

What are some common challenges faced by Dagster engineers when orchestrating complex data pipelines?

Dagster engineers often encounter challenges related to managing dependencies between diverse data assets and ensuring pipeline reliability at scale. Debugging and monitoring can become complex as pipelines grow, particularly when integrating with multiple external systems or deploying in distributed environments. Collaborating closely with data scientists, analysts, and DevOps teams is essential to address these issues, streamline workflows, and maintain data quality. Staying updated with Dagster's evolving features and best practices also helps engineers proactively tackle these challenges.
More about Dagster jobs
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Data Architect - Active Metadata

$65.25 - $84/hr

Other

Posted 5 days ago


Job description

Data Architect

Location: Menlo Park, CA (Remote)

Note: Education M.S./Ph.D. in Computer Science (Formal Methods/Logic) or Computational Mathematics.

Role Overview: We are seeking a visionary to architect a Self-Healing, Autonomous Data Fabric. You will replace legacy ETL with a "nervous system" where metadata is active, governance is computational, and data sharing is zero-copy.

Mandatory Skills:

  • Active Metadata: Experience building closed-loop automation (e.g., metadata-triggered autonomous schema repair).
  • Semantic Engineering: Mastery of RDF, OWL, and SHACL for ontology-first modeling and SPARQL reasoning.
  • Production-level Open Policy Agent (OPA)/ Policy-as-Code (Zero-Trust) for dynamic, context-aware access control.

Other Technical Skills:

  • Advanced Privacy: Implementation of Homomorphic Encryption (FHE) or SMPC for analytics on encrypted PII.
  • Zero-Copy Architecture: Expertise in Delta Sharing for cross-cloud analytics without egress.
  • Compute: Trino (GraalVM), StarRocks, DuckDB (WASM).
  • Orchestration: Dagster, Airflow (Provider-level).
  • Semantic Layer: Stardog, Apache Jena, GraphQL Federation.
  • System Languages: Rust, Clojure, or Java.