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Dagster Jobs (NOW HIRING)

Blue Learning

Data Engineer

Lewisville, TX · On-site

$75K - $93K/yr

Use Dagster to schedule, monitor, and manage workflows, ensuring errors are caught early. * Database Management: Work across both SQL Server and Google BigQuery , managing data structures and ...

Group1001

Staff ML Engineer

Zionsville, IN · On-site

Snowflake, Dagster, Coalesce, Palantir and AWS SageMaker. This role is for engineers who are as passionate about infrastructure, deployment, and operationalizing ML as they are about the models ...

Billee.AI

Senior Data Engineer

Dallas, TX · Remote

$108K - $147K/yr

Dagster * Transformation: DBT * Language: Python, SQL * Cloud: Azure * Adjacent: Hex, MCP Requirements * 4+ years in data platform engineering. Bonus if you've been a primary builder on a platform ...

Group1001

Staff ML Engineer

Zionsville, IN · On-site

Snowflake, Dagster, Coalesce, Palantir and AWS SageMaker. This role is for engineers who are as passionate about infrastructure, deployment, and operationalizing ML as they are about the models ...

Arya Health

Senior Software Engineer, Data

New York, NY · On-site

$160K - $230K/yr

Architect, build, and maintain ETL/ELT pipelines using Airbyte, Dagster, or similar frameworks. * Integrate with REST, GraphQL, and file-based APIs, as well as RPA workflows. * Optimize Postgres ...

Arlo

Data Engineer

Manhattan, NY · On-site

$126K - $151K/yr

... Dagster or Airflow, ensuring reliable scheduling, retries, and alerting • Build monitoring and alerting for data inconsistencies: duplicate records, mismatched member IDs, enrollment timing gaps ...

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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.
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Dagster jobs near you
Infographic showing various Dagster job openings in the United States as of July 2026, with employment types broken down into 97% Full Time, and 3% Contract. Highlights an 74% Physical, 2% Hybrid, and 24% Remote job distribution.

Forward Deployed Data Engineer with Security Clearance

BOAB Ventures

Groton, CT • On-site

$113K - $136K/yr

Other

Posted 12 days ago

Job description

Job Description We're seeking a skilled Forward Deployed Data Engineer to help build next-generation data management and artificial intelligence platforms supporting maritime domain awareness missions. As a forward-deployed engineer, you'll work directly with customers-writing code, integrating systems, and solving complex technical challenges in operational environments. You'll serve as both an engineer and technical advisor, taking ownership of mission outcomes. This position requires a current or active U.S. Secret clearance. This role offers the opportunity to work on real-world projects involving sensor systems, edge data collection, and large-scale maritime data processing environments that directly support operational mission success. Responsibilities • Implement real-time data pipelines using MQTT and Redpanda for stream processing. • Implement offline data pipelines using Dagster for batch processing. • Parse and process binary message formats from various data sources. • Build data warehouses using PostgreSQL, Apache Iceberg, Parquet, and S3. • Design data models that support high-performance analytical queries. • Validate and normalize diverse data sources. • Improve local development environments and CI/CD workflows using modern tooling and GitHub Actions. Required Skills Required Skills • Expertise in time-series data processing and analysis (windowing, resampling, interpolation, etc.) • Proficiency in Python and Rust for data engineering workflows • Experience with binary message parsing • Experience with row-based and columnar data formats • Experience with OLTP and OLAP databases • Knowledge of distributed systems, streaming architectures, and batch processing patterns • Hands-on experience with workflow orchestration platforms such as Dagster or Airflow • Hands-on experience with streaming platforms such as Redpanda or Kafka • Experience working with binary message formats such as Protobuf Desired Skills Required Skills • Expertise in time-series data processing and analysis (windowing, resampling, interpolation, etc.) • Proficiency in Python and Rust for data engineering workflows • Experience with binary message parsing • Experience with row-based and columnar data formats • Experience with OLTP and OLAP databases • Knowledge of distributed systems, streaming architectures, and batch processing patterns • Hands-on experience with workflow orchestration platforms such as Dagster or Airflow • Hands-on experience with streaming platforms such as Redpanda or Kafka • Experience working with binary message formats such as Protobuf

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