Cloud Data Engineer
Woolpert
AzureCloudJavaScriptPythonSQLTableau
Staff Data Pipeline Engineer
Netlify
full-time
Posted on:
Location Type: Remote
Location: Remote • 🇺🇸 United States
Visit company websiteSalary
💰 $168,000 - $227,000 per year
Job Level
Lead
Tech Stack
AirflowAWSCloudGoGoogle Cloud PlatformGrafanaJavaKafkaMongoDBPythonSQL
About the role
- 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.
Requirements
- 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.
- Preferred but not required: experience with usage-based billing or metering systems, and/or experience with tools like dbt and Airflow for orchestration.
Benefits
- Health insurance
- 401(k) matching
- Flexible work hours
- Paid time off
- Remote work options
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
data pipelinesreal-time streamingKafkaMongoDBSnowflakeClickHouseSQLGoPythonJava
Soft skills
mentoringcommunicationcollaborationprocess improvementinnovationpragmatismcross-functional teamworkdocumentationproblem-solvingleadership
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