Staff Data Engineer

JobNimbus•Lehi, UT

About The Position

As a Staff Data Engineer, you will own the technical architecture and production runtime of JobNimbus's enterprise integration portfolio and external data engine. This is a heavy backend systems-engineering role, not an analyst or dashboard-building position. You will architect real-time stream processing, harden infrastructure to meet strict Enterprise SLAs, build event-driven pipelines that push data directly to global clients, and lead the team through pure automation and infrastructure-as-code. You are the ultimate technical anchor translating data into a high-scale, production-grade product.

Requirements

Heavy Software & Systems Engineering Depth: 8+ years of deep data engineering experience operating past the $50M ARR scale, specifically focused on building external-facing data systems and high-throughput infrastructure (not internal reporting or analytics).
Production Integration Portfolio: A documented history of personally owning, debugging, and maintaining the production runtime of critical customer-facing integration systems, with complete comfort navigating deep change management and 4:00 PM incident escalations.
Advanced AWS Cloud Infrastructure: Expert-level depth across AWS big data workloads, cloud networking (VPC Peering, PrivateLink, Transit Gateway), IAM at scale, Lambda/Step functions, and account-level egress cost optimizations.
Snowflake Internal Mastery: Deep architecture expertise extending well past writing SQL, including cluster optimization economics, multi-account layout, reader-account flows, Iceberg, and secure data sharing.
Strict Terraform Practice: Hands-on experience writing clean, reusable Terraform modules for complex data architectures with strict multi-environment state management and secrets handling.
Event-Driven & Streaming DNA: Direct experience or highly advanced familiarity with event-driven architecture and stream-processing frameworks like Apache Spark, Flink, or Kafka.
Technical Leadership: Proven experience leading broad, cross-functional technical initiatives from design to deployment, alongside a track record of actively leveling up senior engineers.

Nice To Haves

Ownership. You own the outcomes, drive initiatives, and solve problems proactively. If you need direction and someone to hold your hand, this job is not for you.
Customer Obsessed. Everything we build should leave our customers saying, "Aw dip. This product is off the charts cool. Whoever wrote that code deserves a raise!"
Proactive Learning. You stay ahead of the curve, continuously learning and implementing cutting-edge technologies.
Team Commitment. You build, mentor, and lead a high-performance engineering team that delivers results together.
Self Awareness. You know your strengths, weaknesses, and how to surround yourself with the right talent to succeed.

Responsibilities

Harden Production Data Infrastructure: Engineer, scale, and operationalize resilient data systems built to withstand the demands of up-market, enterprise customers and strict system availability SLAs.
Architect Real-Time Streaming Systems: Build and deploy high-performance stream-processing frameworks using tools like Apache Spark or Kafka, ensuring enterprise SLAs are met
Build Event-Driven Integrations: Design, code, and deploy a brand-new backend capability to stream and push system events directly into customer environments as they happen.
Eliminate Click-Ops via IaC: Serve as the core technical expert for the team's AWS architecture, codifying and enforcing all environment changes globally through Terraform module design.
Pioneer Data-Centric AI Services: Architect, build, and deploy Model Context Protocol (MCP) servers and agentic AI workflows embedded directly within core data services.
Enforce Core Engineering Standards: Standardize complex data contracts, schemas, and schemas across broad engineering ecosystems to ensure data served through public APIs is highly synchronized and performant.
Technical Mentorship: Drive the technical progression of the engineering team, mentoring senior data engineers in advanced system architecture, cloud networking, and production reliability.