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Data Engineer Airflow Jobs in Sandy, OR (NOW HIRING)

Data Engineer I, II

Portland, OR · On-site +1

$78K - $110K/yr

Position Summary The Data Engineer role on the Data Science Team (DST) is responsible for designing ... and/or Airflow. Exposure to modern cloud-based transformation tools such as dbt or similar is ...

Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation * Experience with MLOps/LLMOps ...

Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation * Experience with MLOps/LLMOps ...

Develop scalable data and model pipelines on cloud platforms. * Monitor model performance, data ... Familiarity with Apache Airflow, Kafka, or Spark. * Knowledge of feature stores and model ...

Data engineering experience with Spark, Airflow/dbt, streaming, data modeling or ML/data science background feature engineering, experimentation or model evaluation * Experience with MLOps/LLMOps ...

Developer

Portland, OR · On-site +1

$40 - $45/hr

Cloud environments (AWS/Azure) and data tools (Python, Workato, Airflow, Git). ● Modern web ... programming languages and tools (Python, SQL, dbt, Git, etc.) to develop integrations and data ...

Developer

Portland, OR · On-site +1

Cloud environments (AWS/Azure) and data tools (Python, Workato, Airflow, Git). ● Modern web ... programming languages and tools (Python, SQL, dbt, Git, etc.) to develop integrations and data ...

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Showing results 1-20

Data Engineer Airflow information

See Sandy, OR salary details

$46.8K

$136.3K

$186.5K

How much do data engineer airflow jobs pay per year?

As of Aug 11, 2026, the average yearly pay for data engineer airflow in Sandy, OR is $136,319.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,300.00 and $144,500.00 per year, depending on experience, location, and employer.

What is the difference between Data Engineer Airflow vs Data Engineer?

AspectData Engineer AirflowData Engineer
Primary FocusWorkflow orchestration and pipeline automation using AirflowData collection, storage, transformation, and pipeline development
Required SkillsPython, Airflow, ETL processes, cloud platformsSQL, Python, ETL, data modeling, cloud services
Work EnvironmentData teams, cloud environments, automation pipelinesData warehouses, big data platforms, cloud infrastructure
CertificationsAirflow certifications, Python, cloud certificationsSQL, cloud certifications, data engineering certifications

While both roles involve data pipeline work, Data Engineer Airflow specializes in designing and managing workflows with Airflow, focusing on automation and orchestration. In contrast, Data Engineer has a broader scope, including data storage, transformation, and pipeline development across various tools and platforms.

What does a data engineer specializing in Airflow do?

A Data Engineer specializing in Airflow is responsible for designing, building, and maintaining data pipelines using Apache Airflow, an open-source workflow orchestration tool. Their main job is to automate, schedule, and monitor complex data workflows, ensuring data moves reliably between systems and is processed efficiently. They often collaborate with data scientists, analysts, and other engineers to make sure that data is accessible, accurate, and up to date for business needs. Expertise in Airflow helps streamline data operations, optimize performance, and improve data pipeline reliability.

What are the key skills and qualifications needed to thrive as a data engineer specializing in Airflow, and why are they important?

To thrive as a Data Engineer with an Airflow focus, you need strong programming skills in Python, expertise in data pipeline design, and experience with distributed systems, often supported by a degree in computer science or a related field. Familiarity with Apache Airflow, cloud platforms (like AWS or GCP), and database technologies, as well as certifications in cloud data engineering, are typically required. Outstanding problem-solving, attention to detail, and effective communication help you collaborate on complex data workflows and troubleshoot issues efficiently. These skills ensure robust, scalable, and reliable data infrastructure, enabling organizations to make data-driven decisions with confidence.

How does a data engineer specializing in Airflow typically collaborate with data scientists and analysts?

Data Engineers working with Airflow play a crucial role in enabling data scientists and analysts to access reliable, up-to-date data. They design and maintain ETL pipelines that automate data movement and transformation, ensuring data is clean and available for analysis. Collaboration often involves gathering requirements, troubleshooting pipeline issues, and optimizing data workflows to meet the needs of downstream users. Effective communication and documentation are essential, as data engineers must align technical solutions with the analytical goals of the broader team.
What cities near Sandy, OR are hiring for Data Engineer Airflow jobs? Cities near Sandy, OR with the most Data Engineer Airflow job openings:
Infographic showing various Data Engineer Airflow job openings in Sandy, OR as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $136,319 per year, or $65.5 per hour.

$120K - $144K/yr

Full-time

This job post has expired today. Applications are no longer accepted.


Job description

Hi All,
Hope you are doing great!
This is Himabindu from Rootshell Inc. We have an immediate need for below mention requirement, if you feel that you are a perfect match to this requirement, please forward your most updated resume along with the best time and number to carry out further discussions.
Looking forward to hear from you...
Role: Big Data Engineer
Location: Portland OR
Position:Long term
Role Expectations:
Strong experience in Scala or Python.
Experience building domain-driven microservices.
Experience with data modeling in different data stores and the Hadoop ecosystem. -
Experience working with data stores such as Snowflake, DynamoDB, etc. -
Experience working with Big Data frameworks such as Spark, Hive, Nifi, Spark-streaming, Kinesis, Kafka, etc. -
Experience with performance and scalability tuning. -
Experience working with schema evolution, serialization, and validation with file formats such as JSON, Parquet, Avro, etc.
Experience working in the AWS environment, specifically S3 and EMR. - Experience working with Airflow.
Familiarity with practices such as CI/CD and Automated testing.
Agile/Scrum Application development experience.
An interest in artificial intelligence and machine learning.