Staff Data Platform Engineer (Remote)

Webflow; Oregon; Hybrid; USD 213,000 - 255,000; Full time

Benefits offered by this job

Equity (RSUs)

Health coverage

Paid parental leave

Flexible vacation

Mental health resources

401(k) with employer match

Job summary

Webflow is seeking a Staff Data Engineer to own and drive data platform initiatives, spanning batch, streaming, and real-time workloads. You will design scalable data pipelines using Spark, Kafka, Iceberg, and Airflow, and help evolve the data lake, governance, and residency to meet GDPR/CCPA needs.

Lead end-to-end data engineering programs, mentor engineers, and collaborate with Analytics Engineering to push reliability and quality across datasets.

Qualifications

• BA/BS degree or equivalent experience.
• 5+ years experience in data engineering.
• Strong experience with Spark and distributed data processing.
• Experience with Kafka, Spark Structured Streaming, and CDC.
• Experience with cloud data infrastructure and IaC.
• Proven leadership of complex data engineering initiatives end-to-end.
• Strong programming and SQL skills.

Responsibilities

• Design data solutions across batch, streaming, and real-time workloads.
• Build, maintain and scale cloud data infrastructure with Kafka, Airflow, Druid, EMR on EKS.
• Improve data quality, observability, reliability, and governance across pipelines.
• Lead complex data engineering initiatives end-to-end and mentor engineers.
• Develop agent harness capabilities to encode standards into AI tools.

Skills

Spark

Kafka

SQL

Python

Data pipelines

Cloud infra

CI/CD

Leadership

Education

BA/BS degree or equivalent

Tools

Airflow MWAA

Iceberg

EMR on EKS

Druid

Job description

Webflow is seeking a Staff Data Engineer to own and drive data platform initiatives, spanning batch, streaming, and real-time workloads. You will design scalable data pipelines using Spark, Kafka, Iceberg, and Airflow, and help evolve the data lake, governance, and residency to meet GDPR/CCPA needs.

Lead end-to-end data engineering programs, mentor engineers, and collaborate with Analytics Engineering to push reliability and quality across datasets.