Senior Software Engineer - Data Pipelines

Who is Tenable?

Tenable® is the Exposure Management company. Over 40,000 organizations around the globe rely on Tenable to understand and reduce cyber risk. Our global employees support 65 percent of the Fortune 500, 50 percent of the Global 2000, and large government agencies. Come be part of our journey!

What makes Tenable such a great place to work?

Ask a member of our team and they’ll answer, “Our people!” We work together to build and innovate best-in-class cybersecurity solutions for our customers; all while creating a culture of belonging, respect, and excellence where we can be our best selves. When you’re part of our #OneTenable team, you can expect to partner with some of the most talented and passionate people in the industry, and have the support and resources you need to do work that truly matters. We deliver results that exceed expectations and we win together!

Your Role

• You'll own the whole lifecycle of data pipelines running in 15+ regions, from design through production, and set the technical direction for how we build them.
• You'll write and optimize big, distributed processing jobs to handle massive datasets.
• You'll build and maintain pipelines that feed our product's access layer—think threat intelligence, assets, and detections—and evolve the data models underneath them.
• Quality is huge: you'll design frameworks to check data health, run conditional checks, and keep everything observable.
• You'll lead our observability across all pipelines.
• You'll raise the engineering bar through design reviews, code review, and mentorship.
  
  

• We believe in owning your work end-to-end without annoying bottlenecks.
• We're AI-native, using custom plugins and protocols to make development smoother.
• We take engineering rigor seriously (think dead-code detection, constant security scans, and always-on production monitoring).
• Yes, we have on-call, but we've built tools to automate the pain out of it—and we expect you to keep automating.
  
  

• 7+ years building and operating production data pipelines at scale, including systems you designed yourself and then ran.
• Deep Python 3.10+ chops (Pydantic, async, decorators, packaging, profiling).
• Apache Airflow in production DAG authoring at scale, dynamic task mapping, deferrable operators, SLAs, MWAA or self-hosted operations and upgrades.
• PySpark mastery job authoring plus real optimization (partitioning, shuffle and skew mitigation, join strategy, reading Catalyst plans), EMR or Databricks.
• Snowflake depth (Snowpark, schema and clustering design, query tuning, warehouse sizing, cost attribution).
• AWS knowledge (S3, SQS/SNS, EMR, IAM, infrastructure-as-code).
• Data quality tooling experience designing frameworks (Great Expectations or equivalent), not only configuring them.
• Observability: distributed tracing, structured logging, metrics.
• CI/CD with artifact packaging and staged deployments across many environments and regions.
• Strong testing discipline: pytest, moto, integration tests against real or mocked cloud services.