Staff Data Engineer

Webflow is an agentic web marketing platform for modern marketing teams, helping organizations build, manage, and optimize high-performing web experiences. The Staff Data Engineer will lead key Data Platform Engineering initiatives involving data lakes, event instrumentation, data quality, and governance, while designing and operating scalable batch, streaming, and real-time data systems.

Responsibilities:

• Design data solutions across batch, streaming, and real-time workloads
• Design and build reliable data pipelines using Spark, Kafka, Iceberg, and Airflow/MWAA
• Contribute to the evolution of data lake and data platform, including ingestion, processing, storage, and serving patterns
• Build, maintain and scale cloud data infrastructure that includes Kafka, Airflow, Druid, EMR on EKS with reliability and observability in mind
• Implement and improve data quality, observability, reliability, and governance across data pipelines and systems
• Define and improve standards for event instrumentation and governance, including event schemas, validation, and schema evolution
• Build platform solutions for centralized PII handling, data retention, deletion, and residency to support GDPR and CCPA requirements
• Build agent harness capabilities that encode data engineering standards, pipeline patterns, and quality gates into AI tools, enabling agents to safely generate, review, and operate on data platform code
• Contribute hands-on to complex technical initiatives, troubleshoot production issues, mentor engineers, and collaborate with Analytics Engineering and other teams
• Build agent harnesses that embed data engineering standards, pipeline patterns, and quality gates into AI-assisted development workflows

Requirements:

• • Location: Remote-first (United States)
• • BA/BS degree or equivalent experience
• • 5+ years of experience in data engineering, building and operating production data pipelines and platforms
• • Strong experience with Spark and distributed data processing, including designing and optimizing production data pipelines
• • Experience designing batch, real-time, and streaming data solutions using technologies such as Kafka, Spark Structured Streaming, and CDC
• • Experience implementing data quality, observability, and reliability across production data systems
• • Experience with cloud data infrastructure, CI/CD, and infrastructure-as-code
• • Demonstrated experience leading complex data engineering initiatives end-to-end, from technical design and decomposition through implementation and production
• • Strong Programming and SQL skills, with experience building reliable and maintainable data systems
• • Can navigate ambiguous problems, evaluate architectural tradeoffs, and make pragmatic technical decisions
• • Think beyond individual pipelines and consider the end-to-end data ecosystem, from data producers through downstream consumers
• • Bring experience with data governance and privacy, including PII management, retention, deletion, data residency, GDPR, or CCPA
• • Bring experience with event instrumentation and governance, including event schemas, validation, and schema evolution
• • Collaborate with engineers on complex technical problems and help establish practical engineering best practices
• • Embrace AI and emerging technologies, applying them in your development workflow and helping the team adopt new tools through shared learnings and best practices
• • Stay curious and open to growth  demonstrating a proactive embrace of AI, and actively building and applying fluency in emerging technologies to elevate how we work, drive faster outcomes, and expand collective impact
• To join Webflow, you'll need a valid right to work authorization depending on the country of employment.