> Markdown version of [/jobs/ext/2290485-senior-staff-data-platform-reliability-engineer](https://www.wearedevelopers.com/jobs/ext/2290485-senior-staff-data-platform-reliability-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Staff Data Platform Reliability Engineer - **Company:** Workiva, Inc. - **Location:** Ames, IA, United States (Remote available) - **Experience:** Expert - **Salary:** $151,000.0 - $242,000.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Airflow, Amazon Web Services, Amazon S3, Data Analysis, Systems Engineering, BigQuery, Cloud Computing, Computer Programming, Information Engineering, Data Governance, Data Infrastructure, Data Integrity, Extract Transform Load (ETL), Data Warehousing, DevOps, Distributed Systems, Monitoring of Systems, Python (Programming Language), OpenFlow, Role-Based Access Control, Site Reliability Engineering Practices, DataOps, Service-Oriented Architecture, Data Processing, Snowflake, Data Lakes, Kubernetes, Information Technology, Terraform, Splunk, Data Pipelines, Docker, Databricks, Programming Languages - **Published:** August 29, 2026 - **Apply:** https://jobs.localjobnetwork.com/apply/add/87023131/1 ## About the Role \* Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience \* Experience: 6+ years of experience in SRE, DevOps, or Systems Engineering roles, with a deep focus on data infrastructure, including experience leading technical projects or teams \* Technical Direction: Proven ability to provide clear technical leadership, direction, and oversight to cross-functional or geographically distributed engineering teams (e.g., contract or offshore teams) \* Data Expertise: Deep understanding of data modeling, warehousing, and building scalable ETL/ELT pipelines \* Data Warehouse: Hands-on experience with Snowflake and DBT a must. Expert in Snowflake SQL. \* Monitoring and Automation: Expert-level hands-on experience with Terraform, Splunk, and Airflow or similar technologies required \* Programming: High proficiency in Python and programming languages such as Java, Go, or Scala \* Ingestion Frameworks: Management of ingestion frameworks like Fivetran, CData, Census and Openflow \* Data Lakes: Experience with S3, Athena and Iceberg required, \* Infrastructure: Extensive experience with Kubernetes, Docker, and cloud-managed services (AWS preferred) \* Systems Knowledge: Familiarity with Unix/Linux system internals, networking, and distributed systems \* Scale: Experience in designing, analyzing, and operating large-scale distributed systems and massive data warehouses \* SRE Maturity: Strong background in cost optimization, usage governance, and maturing SRE practices within a data ecosystem Working Conditions & Travel Requirements \* Minimal (\<10%) travel for team jams or engineering wide conferences \* Reliable internet access for remote working opportunities Workiva will not provide visa sponsorship for this position. Candidates must be authorized to work in the U.S. on a permanent basis. ## Description * 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) * Compliance: Partnering with Legal/Security teams to ensure data handling meets GDPR, CCPA, or industry-specific regulations (HIPAA, SOX) Strategic Stakeholder Management * Capacity Planning:Managing the cloud budget (Snowflake/BigQuery/Databricks costs) and predicting how much compute power the company will need as data volume grows * Business Alignment:Translating technical constraints into business impact. If a project is delayed, they explain why in terms of risk and data integrity rather than just "the code broke" * Operational Support:Consult with and provide expert operational support to data engineering, product teams, and stakeholders who utilize the Data Platform. This is critical to ensuring the performance and reliability of downstream data products, Workiva employees are required to undergo comprehensive security and privacy training tailored to their roles, ensuring adherence to company policies and regulatory standards. ## Related Videos - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Our journey with Spring Boot in a microservice architecture](https://www.wearedevelopers.com/videos/511-our-journey-with-spring-boot-in-a-microservice-architecture) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) - [DevOps Maturity Check – a way to balance autonomy and alignment](https://www.wearedevelopers.com/videos/58-devops-maturity-check-a-way-to-balance-autonomy-and-alignment) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Fully Remote Software Engineer Jobs](https://www.wearedevelopers.com/magazine/447-fully-remote-software-engineer-jobs) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Does The Tech Industry Have The Best Work-life Balance?](https://www.wearedevelopers.com/magazine/427-does-the-tech-industry-have-the-best-work-life-balance)