Staff / Principal Data Engineer

AppGate

Staff Data Engineer responsible for AI-native data platform and data lake supporting fraud detection at AppGate. Collaborating with engineers, data scientists, and product partners to ensure effective data operations.

Posted 6/12/2026full-timeNew York City • New York • 🇺🇸 United StatesLead💰 $180 - $270 per yearWebsite

Tech Stack

Tools & technologies

ApacheKubernetesSpark

About the role

Key responsibilities & impact

Own the design, build and operation of the data lake and ingestion platform end-to-end, from architecture through production reliability.
Build low-latency batch and streaming pipelines that ingest signals from internal and external sources, normalize them to a common schema, enrich them with context and serve model-ready data to the layers above.
Make adding a new data source a routine task rather than a project, so our view of risk keeps widening over time.
Establish data quality, freshness, completeness, lineage and observability so the platform is trustworthy enough to automate on top of.
Build data pipelines that ground generative AI, including unstructured text and threat intelligence processing, embedding generation, vector storage and retrieval.
Own deployment, CI/CD and operational reliability of the platform on Kubernetes.
Partner with data science, product and architecture to turn the platform into a shared foundation across 360 Fraud Protection.

Requirements

What you’ll need

Extensive experience building and operating large-scale data platforms and data lakes, with comfort working at high data volumes.
Deep, hands-on expertise with Apache Spark, Apache Flink and modern big-data systems.
Proven command of best practices for building and maintaining data pipelines in both batch and streaming modes.
Strong production engineering skills across the full delivery lifecycle, including Kubernetes and CI/CD tooling, with the ability to ship end-to-end.
A track record of owning data infrastructure end-to-end with limited supervision.

Benefits

Comp & perks

🌐 Worldwide ❌ Jobs You've Hidden ⭐️ Saved Jobs ✅ Applied Jobs ✉️ Email Alerts 👤 Account AppGate Website LinkedIn All Job Openings 501 - 1000 employees 🔒 Cybersecurity 🏢 Enterprise Cybersecurity
Enterprise AppGate is a global cybersecurity company that delivers high-performance Zero Trust Network Access (ZTNA) solutions for enterprises and government agencies. Its platform enforces identity-based, adaptive access policies using real-time risk scoring, AI-powered application discovery, and a direct-routed architecture designed to avoid cloud bottlenecks and scale with demanding environments. AppGate also provides professional services and cyber advisory offerings — including adversary simulation, penetration testing, and third-party access risk assessments — to help organizations implement and operationalize Zero Trust controls. Staff / Principal Data Engineer Job not on LinkedIn 🔥 20 minutes ago 🏢🏡 New York City – Hybrid 💵 $180 - $270 / year ⏰ Full Time 🔴 Lead 🚰 Data Engineer Apache Kubernetes Spark Apply Now Find Hiring Managers Customize resume + cover letter Report problem ☆ Save ☑️ Mark as applied ❌ Hide 📋 Description
Own the design, build and operation of the data lake and ingestion platform end-to-end, from architecture through production reliability.
Build low-latency batch and streaming pipelines that ingest signals from internal and external sources, normalize them to a common schema, enrich them with context and serve model-ready data to the layers above.
Make adding a new data source a routine task rather than a project, so our view of risk keeps widening over time.
Establish data quality, freshness, completeness, lineage and observability so the platform is trustworthy enough to automate on top of.
Build data pipelines that ground generative AI, including unstructured text and threat intelligence processing, embedding generation, vector storage and retrieval.
Own deployment, CI/CD and operational reliability of the platform on Kubernetes.
Partner with data science, product and architecture to turn the platform into a shared foundation across 360 Fraud Protection. 🎯 Requirements
Extensive experience building and operating large-scale data platforms and data lakes, with comfort working at high data volumes.
Deep, hands-on expertise with Apache Spark, Apache Flink and modern big-data systems.
Proven command of best practices for building and maintaining data pipelines in both batch and streaming modes.
Strong production engineering skills across the full delivery lifecycle, including Kubernetes and CI/CD tooling, with the ability to ship end-to-end.
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Hard Skills & Tools

data lakedata ingestiondata pipelinesApache SparkApache FlinkKubernetesCI/CDdata qualitydata lineagedata observability

Soft Skills

production engineeringcollaborationproblem-solvingindependence