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Dagster Jobs (NOW HIRING)

Fluid Consulting Services

DATA ENGINEER

Boulder, CO · Remote

$130K/yr

Contribute to orchestration design and implementation (Airflow, Dagster, Prefect) * Support DBT development and CI/CD practices * Tune BigQuery performance and manage access/security controls

Copart, Inc.

Sr. Data Engineer

Dallas, TX · On-site

$113K - $136K/yr

Hands-on experience with workflow orchestration platforms (Apache Airflow, Prefect, Dagster, Cloud Composer). * Proficiency in BI/Analytical tools (Tableau, Looker, OBIEE, Power BI). * Strong ...

Profound

Data Engineer

New York, NY · On-site

$140K - $260K/yr

Optimize performance and costs across Snowflake, Clickhouse, AWS, dbt, and Dagster * Own data quality by implementing monitoring, alerting, and validation * Manage and extend infrastructure ...

US Mobile

Analytics Data Engineer

New York, NY · On-site

$140K - $190K/yr

Design, build, document, and maintain reliable data pipelines using dbt, Dagster, Redshift, and related tools. * Transform raw data into trusted, canonical datasets for reporting, analysis ...

Chestnut

Software Engineer (Mid-Level)

Seattle, WA · On-site

K8s, ArgoCD, Kargo, Temporal, Dagster * Data: Postgres, Dynamo, Snowflake Benefits * Competitive salary and equity, with 10 year exercise window for stock options * Remote-first culture built on ...

Fluid Consulting Services

DATA ENGINEER

Boulder, CO · Remote

$130K/yr

Contribute to orchestration design and implementation (Airflow, Dagster, Prefect) * Support DBT development and CI/CD practices * Tune BigQuery performance and manage access/security controls

Apple

Data & Analytics Engineer, AiDP

Austin, TX

$113K - $136K/yr

... Dagster Optimize pipelines and queries for performance, scalability, and cost efficiency Contribute to the design of the data architecture supporting AI agents and autonomous workflows Enable self ...

TMS

Data Architect - Active Metadata

Menlo Park, CA · Remote

$90 - $95/hr

Dagster, Airflow (Provider-level). - Semantic Layer: Stardog, Apache Jena, GraphQL Federation. - System Languages: Rust, Clojure, or Java. Note Education M.S./Ph.D. in Computer Science (Formal ...

datafuelX Inc.

Sr Data Engineer

New York, NY · Hybrid

$125K - $150K/yr

Build, optimize, and maintain ETL/ELT processes for both batch and near-real-time workloads, orchestrated with modern workflow tools (e.g., Airflow, Dagster). * Collaborate with machine learning ...

datafuelX Inc.

Sr Data Engineer

New York, NY · On-site

$125K - $150K/yr

Build, optimize, and maintain ETL/ELT processes for both batch and near-real-time workloads, orchestrated with modern workflow tools (e.g., Airflow, Dagster). * Collaborate with machine learning ...

Zocdoc

Staff Analytics Engineer

New York, NY

Architecting and developing production-grade data transformations and models using SQL, DBT, and Dagster, ensuring optimal performance, maintainability, scalability, and reliability * Collaborating ...

US Mobile

Analytics Data Engineer

New York, NY

$140K - $190K/yr

Design, build, document, and maintain reliable data pipelines using dbt, Dagster, Redshift, and related tools. * Transform raw data into trusted, canonical datasets for reporting, analysis ...

Infovision

AI Engineer

Dallas, TX · On-site

... Dagster) Experience designing Semantic Layers -- ontologies, embeddings, and semantic search to connect structured and unstructured data Hands-on building AI Chatbots and conversational agents ...

Kikoff

Senior Data Engineer

San Francisco, CA · On-site

$124K - $169K/yr

... Dagster etc • Experience working with DS team • A humble collaborative can-do attitude and natural curiosity Company : Kikoff provides credit building services through secured cards and rent ...

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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.
Quick Reminder - DataOps & Build Engineer - Remote - USA

Quick Reminder - DataOps & Build Engineer - Remote - USA

Lorven Technologies

Remote

$117K - $140K/yr

Full-time

Posted 12 days ago

Job description

Role: DataOps & Build Engineer
Data Analytics
Location: Remote - USA
Project Duration: 6 to 9 Months of contract
We are seeking an experienced and visionary DataOps & Build Engineer to lead the architecture and optimization of a next-generation data platform.
This critical role requires 8+ years of expertise to drive technical direction, mentor teams, and automate complex CI/CD pipelines in a fast-paced environment.
You will be instrumental in bridging development and operations to ensure a scalable, high-performance data lifecycle that powers enterprise-level decision-making.
Key Responsibilities:
  • Establish DataOps Framework: Define, document, and champion the organizational framework and guidelines for DataOps-including release management processes, environment promotion strategy, and data quality standards.
  • Best Practice Dissemination: Create and enforce standard operating procedures (SOPs) for data pipeline development, CI/CD, and testing across the engineering teams, ensuring consistency and adherence to architectural standards
  • Data Pipeline Automation: Design and implement robust continuous integration and continuous delivery (CI/CD) pipelines for data code and infrastructure
  • Workflow Orchestration Implementation: Configure, optimize, and manage the deployment of data workflows using orchestrators such as Dagster or Talend, focusing on automated testing and deployment steps.
  • Version Control & Repository Management: Enforce best practices for source code management (e.g., Gitflow), branching strategies, and repository organization across all data projects.
  • Infrastructure as Code (IaC): Work with Infrastructure teams to automate provisioning and management of data platform resources efficiently within AWS.
  • Resilience and Failure Recovery: Design and implement automated rollback and self-healing mechanisms within pipelines to quickly recover from transient failures.
  • Monitoring and Logging: Set up comprehensive monitoring, logging, and alerting using Cloud native tools, or other tools to ensure visibility into pipeline performance and quickly identify and resolve issues
  • Security and Compliance: Ensure data security and compliance by implementing IAM policies, encryption, and other security measures in AWS, adhering to best practices for handling sensitive data
  • Testing Frameworks: Implement automated testing strategies across the data lifecycle, including unit tests, integration tests, and data quality validation checks (e.g., column integrity, schema drift) to ensure data reliability before deployment
  • Resource and Cost Optimization: Implement automated policies and monitoring to track and control cloud resource consumption, ensuring that pipelines run efficiently and cost-effectively

Candidate Profile:
  • 8+ years of hands-on experience in Data Engineering, DevOps, or a dedicated DataOps role, focused heavily on automation and operational excellence
  • Proven experience implementing CI/CD practices specifically for data pipelines and data infrastructure
  • Strong conceptual understanding of data warehousing, ETL/ELT methodologies, and cloud-native architecture.
  • Automation First Mindset: A strong drive to automate repetitive tasks and eliminate manual intervention in the data lifecycle
  • Collaboration: Excellent communication skills, capable of working effectively with Data Engineers, Data Scientists, and Infrastructure teams
  • Insurance industry experience preferred but not mandatory
  • Tools:
    • Cloud Environment: AWS (S3, IAM, VPC, etc.)
    • Pipeline Build: Dagster or Talend
    • Ingest & Transform: dbt Core, AWS Glue, or Flexter
    • Streaming/Integration: Confluent or AWS Streaming Services
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About Lorven technologies

Sourced by ZipRecruiter

Lorven Technologies, headquartered in Plainsboro, New Jersey, United States, is a reputable company in the technology industry, specializing in providing effective IT solutions and consulting services. The company's official website, lorventech.com, offers comprehensive insights into its offerings which include but are not limited to software development, IT consulting, project management, and business analysis. Since its inception, Lorven Technologies has been committed to ensuring efficiency and reliability in delivering IT services to its global clientele, establishing itself as a trusted name in the industry.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Plainsboro, NJ, US

Year founded

2001

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