Data Operations Lead

At Workiva, we are building the data foundation for the next generation of AI‑enabled platform. Our Data Platform Ops team merges software development with infrastructure operations to design and manage large‑scale data systems. We are looking for a Data Operations Lead to ensure the reliability, scalability, and operational excellence of our analytics and data systems.

• Provide expert technical guidance and direction to an offshore contract team, ensuring high‑quality execution of platform operations, automation, and reliability projects.
• 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.
• Lead incident response and management for platform‑related production issues, conduct blameless post‑mortems, and drive systemic enhancements in reliability and efficiency.
• Design and implement monitoring frameworks to govern service‑oriented architecture, establish alerting for system health, query behavior, and performance bottlenecks.
• Reduce operational toil by building self‑service workflows, guardrails, and infrastructure‑as‑code solutions, automating administrative tasks and environment provisioning.
• Orchestrate data tasks using tools such as Airflow, Dagster, or Prefect to ensure complex dependencies are handled efficiently.
• Ensure appropriate data access through RBAC and manage data quality frameworks to prevent low‑quality data from reaching the warehouse.
• Partner with Legal/Security teams to meet GDPR, CCPA, HIPAA, SOX, and other regulatory requirements.
• Manage cloud budget for Snowflake, Big Query, and Databricks, and predict compute resource needs.
• Translate technical constraints into business impact, explaining delays in risk and data‑integrity terms.
• Provide expert operational support to data engineering, product teams, and stakeholders to ensure performance and reliability of downstream data products.

• Bachelor’s degree in Computer Science, Engineering, or related technical field, or equivalent experience.
• 6+ years of experience in SRE, Dev Ops, or Systems Engineering, with a focus on data infrastructure.
• Proven ability to provide clear technical leadership and oversight to cross‑functional or geographically distributed teams.
• Deep understanding of data modeling, warehousing, and building scalable ETL/ELT pipelines.
• Hands‑on experience with Snowflake and DBT (expert in Snowflake SQL).
• Expert‑level experience with Terraform, Splunk, Airflow, or similar technologies.
• High proficiency in Python and a programming language such as Java, Go, or Scala.
• Experience managing ingestion frameworks such as Fivetran, CData, Census, Openflow.
• Experience with S3, Athena, Iceberg (Data Lakes).
• Preferred:
  Experience with Kubernetes, Docker, and AWS cloud‑managed services.
• Familiarity with Unix/Linux internals, networking, distributed systems.
• Experience designing, analyzing, and operating large‑scale distributed systems and massive data warehouses.
• Strong background in cost optimization, usage governance, and maturing SRE practices within a data ecosystem.

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