Data Operations Lead
GC-Squared Resources, LLC
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Houston, TX
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Mid-Senior level
Posted March 26, 2026
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Commitments
Responsibilities
- This role will 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:
- Cloud Monitoring & Logging
Commitments
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:
Not Met Priorities
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Requirements
- Implement CI/CD best practices for data pipelines
- 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:
- 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
Preferred Skills
- 7+ years experience in Data Engineering, DataOps, or Data Platform Operations
- Strong hands-on experience with Google Cloud Platform , including:
- GCP : GKE, Compute Engine, Cloud Storage, Pub/Sub (or equivalents)
- Cloud Monitoring & Logging
- BigQuery
- Dataflow
- 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
- 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
Education
- (Not required) – Bachelor’s degree in Business, Information Technology, Computer Science, or a related field.
Brief Description: We are seeking a DataOps Lead on behalf of a client. This role will 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
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