Senior Data Engineer

TENEX.AI • San Jose, CA

28d • Onsite

About The Position

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.

Requirements

• 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, BigQuery, or Redshift.
• Expertise with SQL and relational databases (PostgreSQL, MySQL, etc.).
• Proficiency in at least one data engineering language (Python, Go, Scala, etc.).
• Experience working with cloud platforms (GCP or AWS) and cloud-native data services.
• Experience with orchestration and workflow systems (Airflow, Dagster, Prefect, or similar).
• Strong understanding of data modeling, warehousing principles, and performance tuning.
• Demonstrated ability to own complex projects end-to-end with minimal oversight.
• Excellent communication, collaboration, and problem-solving skills.

Nice To Haves

• Experience with modern analytics engineering frameworks.
• Experience with real-time / streaming data systems (Kafka, Pub/Sub, Kinesis).
• Familiarity with BI & dashboarding tools (Looker, Grafana, etc.).
• Experience preparing datasets for AI/ML workflows, including: Feature engineering Vector databases RAG pipelines
• Prior experience in cybersecurity, security analytics, or security data modeling.
• Experience working in an early-stage startup environment.

Responsibilities

• 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, BigQuery, 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.

Benefits

• Competitive salary and benefits package.
• A culture of growth and development, with opportunities to expand your knowledge in AI, cybersecurity, and emerging technologies.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 51-100 employees