Senior Data Engineer

Company Overview

TENEX is an AI-native, automation-first, built-for-scale Managed Detection and Response (MDR) provider. We are a force multiplier for defenders, helping organizations enhance their cybersecurity posture through advanced threat detection, rapid response, and continuous protection. Our team is composed of industry experts with deep experience in cybersecurity, automation, and AI-driven solutions.

We’re a fast-growing startup backed by Andreessen Horowitz. As an early employee, you’ll help shape our culture and have meaningful ownership over high-impact initiatives. This is a unique opportunity to join a small but well-funded team on the ground floor as we build the next-generation cybersecurity platform.

We are expanding our engineering organization and seeking a Senior Data Engineer to architect and own our data infrastructure. This role is foundational in enabling high-quality analytics, reporting, and AI-driven insights across TENEX.

Culture is one of the most important things —explore our culture deck ex.ai to witness how we embody it, prioritizing the irreplaceable collaboration and community of in-person work. This is an in-person opportunity based in our San Jose, CA office where you will be expected to work out of 4 days a week.

As a Senior Data Engineer
, you will design, build, and scale the data systems that power our cybersecurity platform and internal decision-making. You will own ETL/ELT architecture, develop our data warehouse, define core metrics, and enable analytics for engineering, product, security operations, and leadership teams.

You’ll work across the stack—from ingestion pipelines to transformations to reporting—ensuring our data is reliable, actionable, and trustworthy. This role blends hands-on engineering with strategic influence over how TENEX collects, processes, models, and uses data.

• Design, build, and maintain scalable ETL/ELT pipelines for ingesting and processing large volumes of cybersecurity data.

• Develop and manage data warehouse architectures using platforms such as Snowflake, Big Query, or Redshift.

• Build robust data models and schemas that support analytics, product features, and machine learning workflows.

• Ensure the reliability, scalability, and performance of data infrastructure.

• Define, instrument, and maintain core business and product metrics across the organization.

• Build data marts, semantic layers, and curated datasets for use across engineering, product, operations, and customer-facing analytics.

• Partner with stakeholders to identify data needs and translate them into high-impact data solutions.

• Develop dashboards, automated reporting, and analytics layers using modern BI tools.

• Drive visibility into platform performance, security outcomes, and operational metrics.

• Ensure teams have easy access to accurate, timely insights.

• Establish data validation best practices, monitoring, lineage, and observability.

• Implement automated processes to ensure accuracy, consistency, and resilience across pipelines.

• Maintain clear documentation, metadata, and schema evolution practices.

• Collaborate closely with engineering, product, and security teams to support new features and data-driven capabilities.

• Provide technical input into product design, data instrumentation, and architecture.

• Advocate for data best practices across the organization.

• Evaluate and integrate tools that improve data performance, reliability, and automation.

• Contribute to engineering excellence through tooling, CI/CD for data, testing approaches, and process improvements.

• 5+ years of professional experience in data engineering or equivalent.

• Strong experience building ETL/ELT pipelines and distributed data processing systems.

• Hands‑on experience with cloud data warehouses such as Snowflake, Big Query, or Redshift.

• Expertise with SQL and relational databases (Postgre
  
  SQL, MySQL, etc).

• Proficiency in at least one data engineering language (Python, Go, Scala, etc).

• Experience working with…