Staff Data Pipeline Engineer

Overview

Job Description

Responsibilities

• - Design, build, and optimize high-performance data pipelines that power critical business and customer-facing systems.
• - Implement and maintain real-time streaming pipelines using Kafka and both relational and non-relational databases (MongoDB, Snowflake, ClickHouse) to support operational and analytical use cases.
• - Refactor legacy data systems to improve performance, scalability, and reliability, while ensuring billing systems remain stable and data flows remain accurate for downstream processes.
• - Build robust observability and alerting systems to surface data quality or reliability issues before they impact customers or billing.
• - Contribute to systems engineering efforts within the data organization, emphasizing observability, monitoring, and infrastructure-as-code best practices.
• - Partner closely with Software Engineers, Data Analysts, Data Engineers, and Systems Admins to enable reliable data modeling, reporting, and invoicing across self-serve and enterprise billing environments.
• - Drive architectural decisions and evaluate tooling and frameworks to improve performance and cost efficiency.
• - Mentor other engineers on data pipeline best practices, from instrumentation to consumption.
• - Document architecture, runbooks, and operational processes to ensure cross-team confidence and sustainability.
• - Balance innovation with pragmatism, knowing when to experiment versus stabilize given our small team and large production footprint.
• - Identify and implement internal process improvements: automating manual workflows, optimizing data delivery, and redesigning infrastructure for greater scalability.

Required Skills

• - Extensive experience building and operating real-time, event-driven data processing systems at scale.
• - Hands-on experience managing and scaling Kafka clusters and streaming data pipelines in a production environment.
• - Deep expertise in event streaming architectures and messaging systems (Kafka, Kinesis, or similar).
• - Strong proficiency with Snowflake, ClickHouse and data modeling for analytical and operational workloads.
• - Experience working across multi-cloud environments (GCP and AWS preferred).
• - Proficiency in SQL and programming languages Go, Python, or Java.
• - Familiarity with observability and monitoring tools (Datadog, Grafana, Monte Carlo etc.).
• - Experience with source/version control (Git) and CI/CD workflows for data systems.
• - Demonstrated ability to write production code and design scalable, fault-tolerant data infrastructure.
• - Track record of mentoring engineers, fostering a culture of data reliability, and improving team capabilities.
• - Excellent communication skills and collaborative mindset for working cross-functionally with data, engineering, product and finance teams.

Benefits

• - Robust benefits and participation in Netlify''s equity plan.
• - Opportunity to work on a globally distributed, fully remote team that values autonomy, transparency, and shared ownership.