Staff Data Engineer — Remote, Lead Scalable Data Pipelines

Webflow; San Francisco (CA); On-site; USD 213,000 - 255,000; Full time

Benefits offered by this job

RSUs

WIN bonus program

401(k) with employer match (US)

Parental leave

Job summary

Webflow is seeking a Staff Data Engineer to own initiatives across the Data Platform Engineering team, spanning data lake, governance, and instrumentation. You’ll design data solutions across batch, streaming, and real-time workloads and build scalable cloud data infrastructure with a focus on reliability and observability.

You’ll lead complex data engineering initiatives end‑to‑end, mentor engineers, and collaborate with Analytics Engineering.

Qualifications

• 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.

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.

Skills

Spark

Kafka

Iceberg

Airflow/MWAA

Data governance

Data quality

Observability

CI/CD

Infrastructure-as-code

SQL

Programming

Education

BA/BS degree or equivalent experience

Tools

Spark

Kafka

Iceberg

Airflow/MWAA

EMR on EKS

Job description

Webflow is seeking a Staff Data Engineer to own initiatives across the Data Platform Engineering team, spanning data lake, governance, and instrumentation. You’ll design data solutions across batch, streaming, and real-time workloads and build scalable cloud data infrastructure with a focus on reliability and observability.

You’ll lead complex data engineering initiatives end‑to‑end, mentor engineers, and collaborate with Analytics Engineering.