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Data Engineer Airflow Jobs in Spring, TX (NOW HIRING)

Patterson-UTI

Data Ops Lead NEX

Houston, TX · On-site

Experience with data orchestration frameworks (Airflow preferred) * Experience with Infrastructure as Code (Terraform) * Experience with Azure Devops * Proven experience leading data incident ...

BakerHostetler

Data Solutions Engineer

Houston, TX

$109K - $131K/yr

... Airflow • Azure Logic Apps, Azure DevOps, Power Automate, REST API • Familiarity with Azure OpenAI and Document Intelligence for turning unstructured content into usable data. • Data analysis ...

InterSources Inc

AWS Data Architect

Houston, TX · On-site

$60.75 - $78.25/hr

... and DevOps teams to ensure APIs, data models, connectors, microservices are efficient and ... Redshift, apache airflow, SQS, SNS • Lead architecture of solutions to build self-service ...

Deloitte

Lead Forward Deployed Engineer - AWS

Houston, TX · On-site

$97K - $128K/yr

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 ...

Deloitte

Senior Forward Deployed Engineer- AWS

Houston, TX · On-site

$99K - $137K/yr

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 ...

Deloitte

Forward Deployed Engineer- AWS

Houston, TX · On-site

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 ...

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All JobsData Engineer Airflow JobsData Engineer Airflow Jobs in Spring, TX

Data Engineer Airflow information

See Spring, TX salary details

$39.6K

$115.4K

$158K

How much do data engineer airflow jobs pay per year?

As of Sep 8, 2026, the average yearly pay for data engineer airflow in Spring, TX is $115,433.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,900.00 and $122,400.00 per year, depending on experience, location, and employer.

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.

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 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.

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 are popular job titles related to Data Engineer Airflow jobs in Spring, TX?

For Data Engineer Airflow jobs in Spring, TX, the most frequently searched job titles are:

What job categories do people searching Data Engineer Airflow jobs in Spring, TX look for?

The top searched job categories for Data Engineer Airflow jobs in Spring, TX are:

What cities near Spring, TX are hiring for Data Engineer Airflow jobs?

Cities near Spring, TX with the most Data Engineer Airflow job openings:

Data Engineer Airflow jobs near you

Data Ops Lead NEX

Patterson-UTI

Houston, TX • On-site

Full-time

Posted 20 days ago

Patterson-UTI rating

5.0

Company rating: 5.0 out of 10

Based on 23 frontline employees who took The Breakroom Quiz

83rd of 87 rated oil and gas companies

Job description


Brief Description:
We are seeking a DataOps Lead to own and advance the operational reliability, quality, and scalability of our cloud-based data platforms. This role sits at the intersection of data engineering, platform operations, and reliability, supporting critical data pipelines that power analytics, reporting, and operational decision-making across oilfield and energy operations.
The DataOps Lead will be responsible for ensuring that data is available, accurate, timely, and trustworthy, while leading operational best practices across ingestion, processing, and delivery systems running primarily on Google Cloud Platform (GCP).
This is a hands-on technical leadership role with strong expectations for ownership, cross-team collaboration, and continuous improvement.
Detailed Description:
  • Data Platform Operations
    • Own the day-to-day operational health of cloud-based data pipelines and platforms
    • Ensure high data availability, freshness, accuracy, and completeness
    • Lead operational support for batch and streaming data workloads
  • Data Reliability & Quality
    • Define and manage data SLAs, SLOs, and reliability metrics
    • Implement and maintain data quality checks, validations, and monitoring
    • Design processes for backfills, reprocessing, and failure recovery
  • Cloud & Infrastructure
    • Operate and optimize GCP-based data services, including BigQuery, Cloud Storage, Pub/Sub, and GKE
    • Partner with platform and SRE teams on scalability, performance, and cost optimization
    • Manage data infrastructure using Infrastructure as Code (Terraform)
  • Automation & Tooling
    • Build and maintain Python-based automation for data operations and monitoring
    • Improve reliability and repeatability through standardized tooling and workflows
    • Support and enhance data orchestration platforms (e.g., Airflow / Cloud Composer)
  • Incident Response & Operational Excellence
    • Lead response to data incidents, including triage, mitigation, and root cause analysis
    • Drive post-incident reviews and track corrective actions
    • Create and maintain runbooks, operational documentation, and playbooks
  • CI/CD & Governance
    • Implement CI/CD best practices for data pipelines
    • Promote testing, version control, and deployment standards across data workflows
    • Ensure data platforms align with security, governance, and access control requirements
  • Leadership & Collaboration
    • Act as a technical leader within the DataOps function
    • Partner closely with:
      • Data engineering teams
      • SRE / platform engineering
      • Analytics and business stakeholders
    • Mentor engineers and help raise the operational maturity of the data organization

Required Knowledge, Skills, and Abilities:
  • 7+ years experience in Data Engineering, DataOps, or Data Platform Operations
  • 3+ years experience operating cloud-based data platforms in production
  • Strong hands-on experience with Google Cloud Platform, including:
  • GCP: GKE, Compute Engine, Cloud Storage, Pub/Sub (or equivalents)
  • Cloud Monitoring & Logging
  • BigQuery
  • Dataflow
  • Datastream
  • IAM and networking
  • Composer/AIrflow
  • Kubernetes: deployment, scaling, reliability patterns
  • Observability: GCP Cloud Monitoring, Logging
  • Strong proficiency in Python for data pipelines, automation, and operational tooling
  • Experience with data orchestration frameworks (Airflow preferred)
  • Experience with Infrastructure as Code (Terraform)
  • Experience with Azure Devops
  • Proven experience leading data incident response and operational improvements
  • Strong SQL skills for data analysis and troubleshooting

Minimum Qualifications:
  • Bachelor's degree in Business, Information Technology, Computer Science, or a related field.
  • 7+ years experience in Data Engineering, DataOps, or Data Platform Operations
  • 3+ years leading or owning production data platforms in a cloud environment
  • Demonstrated technical leadership of data operations initiatives or teams
  • Ability to understand and speak English at a level of proficiency allowing employee to issue, receive and respond to both safety and operations-related directions in English

Preferred Qualifications:
  • Oil and Gas Industry knowledge
  • Technology/Digital Industry knowledge

#NexTierJob
About Us
The Evolving Oil Field Demands Evolving Service Providers
NexTier is a leading provider of integrated completions that employs sustainable practices and equipment to support our customers' ESG goals while accelerating production in the most demanding US land basins.
Patterson-UTI is committed to a workplace free from discrimination and harassment, offering equal employment opportunities to all individuals regardless of personal characteristics protected by law. Employees are encouraged to report any concerns through multiple channels.

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