DataOps Lead: Cloud Data Reliability & Automation

Brief

Description:

We are seeking a Data Ops 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 Data Ops 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.

• 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 Big Query, 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 Data Ops 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

• 7+ years experience in Data Engineering, Data Ops, 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
  • Big Query
  • 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 Dev Ops
• 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, Data Ops, 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

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