Data Ops Lead

Patterson-UTI • Houston, TX

1d

About The Position

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.

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