Director Data Management

Revolution Technologies; Houston (TX); On-site; USD 180,000 - 260,000; Full time

Benefits offered by this job

Short-Term Disability

Health Savings Account (HSA)

Tuition Reimbursement

401(k)

Life Insurance

Supplemental Insurance Options

Paid Time Off

Job summary

Revolution Technologies seeks a senior Observability & Data FinOps Leader to drive reliability and financial accountability across a large-scale cloud data ecosystem. Leading enterprise Data Observability, FinOps, and platform governance, you will guide a strategic program on GCP and BigQuery while collaborating with data engineering, analytics, and AI/ML teams.

The role emphasizes establishing enterprise standards, roadmaps, and executive reporting to optimize cloud investments and data

Qualifications

• 8+ years leading enterprise data platforms, observability, or DataOps.
• Experience building strategy, roadmaps, operating models, and governance for data platforms.
• Strong background in data reliability, pipeline monitoring, data quality, and incident management.

Responsibilities

• Define and lead enterprise Data Observability and Data FinOps strategy across data engineering, platforms, analytics, and AI/ML.
• Establish a framework for monitoring data pipelines, platform health, data quality, and reliability; set SLAs, SLOs, KPIs, alerts, and root-cause analysis.
• Drive cost visibility, forecasting, allocation, optimization, and financial governance for cloud spend on GCP and BigQuery.
• Identify and implement automated remediation, anomaly detection, and AI-driven observability enhancements.
• Provide executive-level reporting on platform reliability, performance, and cloud cost trends.

Skills

Data Observability

Data Reliability

DataOps Leadership

Cloud Cost Optimization

Leadership & Strategy

Education

Bachelor's degree in Computer Science/Engineering/Data Science

Tools

GCP

BigQuery

Job description

Revolution Technologies is hiring an Observability & Data FinOps Leader for our leading wholesale client!

Join a highly visible enterprise data organization responsible for driving reliability, operational excellence, and financial accountability across a large-scale cloud data ecosystem. This senior leadership role will establish and evolve enterprise Data Observability and Data FinOps capabilities, ensuring data platforms and pipelines are reliable, issues are identified and resolved quickly, and cloud investments are optimized. The environment is primarily Google Cloud Platform (GCP), with a strong focus on BigQuery and modern data and AI platforms.

Key Skills and Experience Required

• Enterprise Data Observability, Data Reliability, and DataOps leadership
• Data FinOps, cloud cost optimization, and financial accountability
• Google Cloud Platform (GCP), BigQuery, and large-scale enterprise data platforms
• Leadership experience establishing strategy, roadmaps, operating models, and enterprise standards

Key Responsibilities

• Define and lead the enterprise Data Observability and Data FinOps strategy across data engineering, data platforms, analytics, AI/ML, and related capabilities.
• Establish an enterprise observability framework for monitoring data pipelines, platform health, data quality, freshness, availability, and reliability.
• Define and operationalize SLAs, SLOs, KPIs, alerting, anomaly detection, and root-cause analysis across critical data platforms and services.
• Develop strategies for proactive issue identification, incident reduction, automated remediation, and continuous improvement.
• Establish Data FinOps practices focused on cloud spend visibility, cost allocation, forecasting, optimization, and financial accountability.
• Drive GCP and BigQuery cost optimization through workload analysis, resource utilization, capacity planning, and platform optimization.
• Evaluate and implement intelligent automation and AI-driven approaches to observability, anomaly detection, root-cause analysis, and remediation.
• Establish executive-level reporting that provides visibility into platform reliability, operational performance, cloud consumption, cost trends, and optimization opportunities.

Required Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, Data Science, or a related technical discipline.
• 8+ years of experience across enterprise data platforms, data engineering, cloud architecture, DataOps, observability, or related disciplines.
• Leadership experience establishing enterprise strategies, roadmaps, operating models, standards, and governance.
• Experience with Data Observability, including data and pipeline monitoring, reliability, data quality, lineage, anomaly detection, alerting, and root-cause analysis.
• Experience with Data FinOps, cloud cost management, cost optimization, financial governance, or large-scale cloud spend management.
• Strong experience with Google Cloud Platform (GCP) and BigQuery in enterprise data environments.

Why Revolution Technologies?

About the Company

Revolution Technologies has been making a difference nationwide since 1993 through premier consulting, staffing, and talent solutions.

We provide strategic consulting, enterprise technology staffing, direct hire, contract-to-hire, and workforce solutions to Fortune 500 organizations across North America. Our consultants support some of the most innovative cloud, AI, digital transformation, and enterprise modernization initiatives in the market today.

Let's Talk About Benefits

Revolution Technologies is proud to offer highly competitive compensation along with a comprehensive benefits package including:

• Short-Term Disability
• Health Savings Account (HSA)
• Tuition Reimbursement
• 401(k)
• Life Insurance
• Supplemental Insurance Options
• Paid Time Off

Equal Opportunity Employer

Revolution Technologies, LLC is an Equal Opportunity Employer and considers all qualified applicants without regard to race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity, genetic information, or any other characteristic protected by applicable law.