Data Operations Lead - Workiva

At Workiva , we are building the data foundation for the next generation of AI-enabled platform. Our Data Platform Ops team is at the center of this mission, merging software development with infrastructure operations to design and manage large-scale.

We are looking for a Data Operations Lead to ensure the reliability, scalability, and operational excellence of our analytics and data systems. This role is operationally critical and technically demanding. As a senior technical leader, you will be responsible for keeping our data platforms available and performant, providing technical direction and guidance to an offshore contract team, and enabling our data engineering teams to move fast with confidence. You will be a key driver of technical strategy and execution without direct people management responsibilities. If you are energized by solving complex data problems at scale and want your work to have a direct impact every day, join us on this transformative journey.

What You'll Do

Operational Excellence and Reliability

Technical Leadership & Direction: Provide expert technical guidance and direction to an offshore contract team to ensure high-quality execution of platform operations, automation, and reliability projects. Act as the primary technical point of contact and decision-maker for the team

Reliability & Operations: Own the operational health and performance of the data platform. Define and implement reliability goals (SLIs/SLOs) and establish sustainable mechanisms for scaling systems through automation

Incident Management: Lead and drive incident response and management for platform-related production issues. Conduct blameless post-mortems and drive systemic enhancements in reliability and efficiency based on findings

Observability & Monitoring: Design and implement monitoring frameworks to govern service-oriented architecture (SOA) efficiently and intelligently. Establish alerting for system health, query behavior, and performance bottlenecks

Procession and Automation (The “Ops” in DataOps)

Automation & Platform Engineering: Reduce operational toil by building self-service workflows, "guardrails," and infrastructure-as-code (IaC) solutions. Automate administration tasks, environment provisioning, and usage monitoring, leveraging and mentoring the offshore team to execute

Orchestration: Managing the "traffic control" of data tasks (using tools like Airflow, Dagster, or Prefect) to ensure complex dependencies are handled efficiently

Data Governance and Security

Access Control: Ensuring the right people have access to the right data (RBAC - Role-Based Access Control) without slowing down the business

Data Quality Frameworks: Building automated "circuit breakers" that stop data from reaching the warehouse if it doesn't meet quality standards (e.g., missing values or incorrect formatting)