DataOps Lead: Cloud Data Reliability & Automation

Patterson-UTI

Houston (TX)

On-site

USD 140,000 - 190,000

Full time

14 days+

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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:
    • 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 proficiency level allowing the employee to issue, receive and respond to operational directions in English
Preferred Qualifications:
  • Oil and Gas Industry knowledge
  • Technology/Digital Industry knowledge
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