Senior DataOps Product Support Engineer

UST

• $96K — $117K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years experience in production data platforms or analytics engineering
  • Proficient with GCP services, focusing on BigQuery and Cloud Composer
  • Strong SQL skills for troubleshooting data issues
  • Experience with Python or similar scripting for automation
  • Knowledge of IAM, access provisioning in cloud environments
  • Familiar with CI/CD processes using GitLab and Terraform
  • Ability to collaborate across technical and business teams

Responsibilities

  • Provide production support for Data Solutions workloads on GCP
  • Monitor and maintain operations of BigQuery, Cloud Composer, and Dataproc
  • Troubleshoot issues with data pipelines and deployments
  • Investigate production incidents using logs and monitoring tools
  • Assess impact and communicate during high-priority incidents
  • Manage and audit IAM roles and dataset permissions
  • Support user access issues across multiple data platforms

Benefits

  • Minimum of 10 days paid vacation per year
  • 6 days of paid sick leave annually
  • 10 paid holidays each year
  • 401(k) Retirement Plan with employer matching
  • Medical, dental, and vision insurance for employees and dependents
  • Company-paid life and disability insurance
  • Health Savings Account (HSA) and Flexible Spending Account (FSA) options
Full Job Description
Role description

Senior DataOps Product Support Engineer

The Role

The Senior DataOps Product Support Engineer is responsible for production support, operational stability, incident response, and service reliability for Data Solutions workloads running on Google Cloud Platform. The engineer will support BigQuery, Cloud Composer, Dataproc, GCS, Pub/Sub, CI/CD deployment processes, access and IAM requests, and validation activities.

What You'll Do
• Provide production support for Data Solutions workloads deployed on GCP, ensuring high availability, operational stability, and timely incident resolution.
• Monitor and support BigQuery, Cloud Composer, Dataproc, GCS, Pub/Sub, and related orchestration and processing components.
• Troubleshoot failed pipelines, delayed data loads, orchestration failures, data freshness issues, and environment-specific deployment problems across dev, cert, and prod.
• Investigate and resolve production incidents using logs, monitoring tools, SQL analysis, job history, and root cause analysis techniques.
• Perform impact assessment, triage, escalation, and stakeholder communication for service interruptions and high-priority incidents.
• Manage and audit GCP IAM roles, BigQuery dataset permissions, service account access, and directory group memberships in accordance with security and compliance requirements.
• Support user and analyst access issues across BigQuery, Databricks, Tableau, and related data access channels.
• Troubleshoot and validate data accuracy, completeness, and delivery across analytical datasets and tables.
• Support production deployments and environment promotions using GitLab-based CI/CD processes and infrastructure changes managed through Terraform.

This position description identifies the responsibilities and tasks typically associated with the performance of the position. Other relevant essential functions may be required.

What You Need
• Strong experience supporting production data platforms or analytics engineering environments
• Hands-on experience with GCP services, especially BigQuery, Cloud Composer, GCS, and Dataproc
• Strong SQL skills and the ability to investigate data issues directly in analytical platforms
• Experience with Python or similar scripting languages for troubleshooting, automation, or operational tooling
• Experience with incident management, production triage, root cause analysis, and operational support processes
• Working knowledge of IAM, access provisioning, service accounts, and dataset-level security in cloud environments
• Experience with CI/CD and infrastructure-as-code practices, preferably using GitLab and Terraform
• Experience supporting data pipelines and orchestration frameworks in production
• Ability to work across technical and business teams, including direct support for analysts and data consumers
• Preferred Qualifications:
• Familiarity with Databricks in an enterprise data platform setting
• Experience supporting Tableau data source migrations or BI platform connectivity issues
• Experience with data reconciliation and validation methodologies
• Exposure to Confluent Cloud, Kafka, or event-driven data integrations
• Experience defining or improving SLOs, ing thresholds, and operational metrics such as MTTD and MTTR
• Experience with Google Cloud certifications (Associate Cloud Engineer, Professional Data Engineer)

Location & Compensation

Compensation can differ depending on factors including but not limited to the specific office location, role, skill set, education, and level of experience. UST provides a reasonable range of compensation for roles that may be hired in various U.S. markets as set forth below.

Role Location: Texas

Compensation Range: $96,000-$117,000

Benefits

Full-time, regular employees accrue a minimum of 10 days of paid vacation per year, receive 6 days of paid sick leave each year (pro-rated for new hires throughout the year), 10 paid holidays, and are eligible for paid bereavement leave and jury duty. They are eligible to participate in the Company's 401(k) Retirement Plan with employer matching. They and their dependents residing in the US are eligible for medical, dental, and vision insurance, as well as the following Company-paid Employee Only benefits: basic life insurance, accidental death and disability insurance, and short- and long-term disability benefits. Regular employees may purchase additional voluntary short-term disability benefits, and participate in a Health Savings Account (HSA) as well as a Flexible Spending Account (FSA) for healthcare, dependent child care, and/or commuting expenses as allowable under IRS guidelines. Benefits offerings vary in Puerto Rico.

Part-time employees receive 6 days of paid sick leave each year (pro-rated for new hires throughout the year) and are eligible to participate in the Company's 401(k) Retirement Plan with employer matching.

Full-time temporary employees receive 6 days of paid sick leave each year (pro-rated for new hires throughout the year) and are eligible to participate in the Company's 401(k) program with employer matching. They and their dependents residing in the US are eligible for medical, dental, and vision insurance.

Part-time temporary employees receive 6 days of paid sick leave each year (pro-rated for new hires throughout the year).

All US employees who work in a state or locality with more generous paid sick leave benefits than specified here will receive the benefit of those sick leave laws.

Similar Jobs

More Jobs at UST

More Information Technology Jobs

Find similar Senior DataOps Product Support Engineer jobs: