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Houston, TX, United States
Live, first seen by us 77 days agoRun day-to-day operations of batch and streaming data pipelines
Define data SLAs, SLOs and reliability metrics
Lead incident triage, root cause analysis and post-incident reviews
Build Python automation for data operations and monitoring
Implement data quality checks, validations and monitoring
Own the day-to-day operational health of cloud-based data pipelines and platforms
Define and manage data SLAs, SLOs, and reliability metrics
Lead response to data incidents, including triage, mitigation, and root cause analysis
Build and maintain Python-based automation for data operations and monitoring
Implement and maintain data quality checks, validations, and monitoring
7+ years experience in Data Engineering, DataOps, or Data Platform Operations
3+ years experience operating cloud-based data platforms in production
Strong proficiency in Python for data pipelines, automation, and operational tooling
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
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Day 77
Up longer than most. Similar jobs usually come down between day 3 and day 43.
From 291 similar postings that came down. Coming down is not always a hire.
2 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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- Automation & Tooling - Build and maintain Python-based automation for data operations and monitoring - Improve reliability and repeatability through standardized tooling and workflows
- Observability: GCP Cloud Monitoring, Logging - Strong proficiency in Python for data pipelines, automation, and operational tooling - Experience with data orchestration frameworks (Airflow preferred)
- Proven experience leading data incident response and operational improvements - Strong SQL skills for data analysis and troubleshooting Minimum Qualifications:
- Experience with Infrastructure as Code (Terraform) - Experience with Azure Devops - Proven experience leading data incident response and operational improvements
- 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
- Cloud Monitoring & Logging - BigQuery - Dataflow
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.
- 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)
- Strong hands-on experience with Google Cloud Platform, including: - GCP: GKE, Compute Engine, Cloud Storage, Pub/Sub (or equivalents) - Cloud Monitoring & Logging
- Kubernetes: deployment, scaling, reliability patterns - Observability: GCP Cloud Monitoring, Logging - Strong proficiency in Python for data pipelines, automation, and operational tooling
- Composer/AIrflow - Kubernetes: deployment, scaling, reliability patterns - Observability: GCP Cloud Monitoring, Logging
- Partner with platform and SRE teams on scalability, performance, and cost optimization - Manage data infrastructure using Infrastructure as Code (Terraform) - Automation & Tooling
- Experience with data orchestration frameworks (Airflow preferred) - Experience with Infrastructure as Code (Terraform) - Experience with Azure Devops
- Improve reliability and repeatability through standardized tooling and workflows - Support and enhance data orchestration platforms (e.g., Airflow / Cloud Composer) - Incident Response & Operational Excellence
- Strong proficiency in Python for data pipelines, automation, and operational tooling - Experience with data orchestration frameworks (Airflow preferred) - Experience with Infrastructure as Code (Terraform)
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New Data Operations postings at the employers we follow are up 227% over the last 5 weeks compared with the 5 before.
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We file this job under Data Operations, by the work the posting describes.
Data operations staff do the day-to-day work of getting data processed correctly: loading and checking files, moving records between systems, fixing errors and following set procedures.
Expect Excel, some SQL, close attention to detail, and knowledge of the particular systems the company runs.
Data governance sets the rules for the data; data operations does the hands-on work of processing it and keeping it moving.
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:
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
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Houston, TX, United States
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