Application Guide
How to Apply for Staff Data Engineer - Platform
at Workiva
🏢 About Workiva
Workiva is a unique company focused on streamlining integrated ESG (Environmental, Social, and Governance) reporting, helping organizations achieve transparent climate impact and compliance. Unlike generic data platforms, Workiva's mission directly addresses the growing demand for sustainability reporting and regulatory compliance. Working here means contributing to technology that helps businesses measure and report their environmental impact—a meaningful intersection of data engineering and social responsibility.
About This Role
As a Staff Data Engineer - Platform at Workiva, you'll architect and build high-performance data solutions that power customer-facing features using Snowflake, dbt, and Kafka. This role is impactful because you'll lead complex data projects from discovery to deployment, directly influencing how customers access and use ESG data. You'll also act as a bridge between product teams and the internal Data Platform team, ensuring data quality and strategic alignment.
💡 A Day in the Life
A typical day might involve collaborating with Product Managers to translate customer needs into technical data requirements, then designing resilient pipelines using DLT and Snowpipe. You could spend time optimizing the dbt layer for high-performance serving in Snowflake, while also mentoring senior engineers through code reviews and technical discussions. Embedded with Application Engineering teams, you'd advocate for upstream data quality and contribute to the Data Platform team's roadmap based on product gaps.
🚀 Application Tools
🎯 Who Workiva Is Looking For
- Has 8+ years of data engineering experience specifically focused on customer-facing products, not just internal analytics.
- Demonstrates proven leadership in large-scale projects from concept to completion with minimal supervision, navigating ambiguity across teams.
- Possesses exceptional ability to evangelize data strategy to non-technical stakeholders (like Product Managers) and influence application engineers on data best practices.
- Has hands-on experience with Snowflake, dbt, Kafka, DLT, and Snowpipe for building resilient, production-grade pipelines at enterprise scale.
📝 Tips for Applying to Workiva
Highlight specific examples where you built data solutions for customer-facing products (not just internal reports) using Snowflake, dbt, and Kafka.
Emphasize projects where you led data initiatives from concept to deployment with minimal supervision, especially in ambiguous or cross-team environments.
Showcase your experience evangelizing data strategy to non-technical stakeholders—mention specific instances where you influenced product or business decisions.
Tailor your resume to include keywords like 'Data-as-a-Product,' 'DLT,' 'Snowpipe,' and 'enterprise-scale workloads' from the job description.
Demonstrate your ability to act as a 'Lead Customer' for a data platform—describe times you identified platform gaps and contributed to roadmap decisions.
✉️ What to Emphasize in Your Cover Letter
["Explain your experience with ESG, sustainability reporting, or compliance data—show how your background aligns with Workiva's mission.", 'Detail a specific project where you architected a high-performance data solution for a customer-facing feature, mentioning technologies like Snowflake and dbt.', 'Describe your approach to evangelizing data strategy to non-technical stakeholders and influencing engineering teams on data best practices.', 'Highlight your leadership in end-to-end data projects, emphasizing how you navigated ambiguity and drove results with minimal supervision.']
Generate Cover Letter →🔍 Research Before Applying
To stand out, make sure you've researched:
- → Explore Workiva's ESG reporting platform and understand how it helps companies with climate impact and compliance—review their website and case studies.
- → Research Snowflake, dbt, and Kafka integrations in enterprise environments, focusing on use cases for customer-facing data products.
- → Learn about ESG reporting standards and regulations (e.g., SEC climate rules, EU CSRD) to understand the domain context of Workiva's products.
- → Investigate Workiva's company culture and values, especially around data excellence and cross-team collaboration, via their blog or employee reviews.
💬 Prepare for These Interview Topics
Based on this role, you may be asked about:
⚠️ Common Mistakes to Avoid
- Focusing only on internal analytics or backend data processing without highlighting customer-facing product experience.
- Failing to demonstrate leadership in end-to-end projects or ability to work with minimal supervision in ambiguous situations.
- Neglecting to show experience with the specific tech stack (Snowflake, dbt, Kafka) or discussing generic data engineering tools instead.
📅 Application Timeline
This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.
Typical hiring timeline:
Application Review
1-2 weeks
Initial Screening
Phone call or written assessment
Interviews
1-2 rounds, usually virtual
Offer
Congratulations!