Data Ops Lead

Patterson-UTI • Houston, TX

3h

About The Position

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

Requirements

• 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
• 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

Nice To Haves

• Oil and Gas Industry knowledge
• Technology/Digital Industry knowledge

Responsibilities

• 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
• 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
• 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)
• 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)
• 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
• 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
• 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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees