Senior Data Engineer | Emerging Products

NinjaOne

4d•$110,000 - $200,000•Hybrid

About The Position

At NinjaOne, we're looking for a skilled Senior Data Engineer to join our Emerging Products team and help build the foundation of our modern data platform. You'll play a critical role in designing and scaling lakehouse architectures, building robust streaming and batch pipelines, and ensuring data flows reliably to the analysts and data scientists who depend on it. This is an exciting opportunity to work on greenfield infrastructure using a cutting-edge stack — Kafka, Spark, Iceberg, and Databricks — collaborate with cross-functional teams, and help shape how we harness data to power our next generation of products. Location — We are flexible on remote working from home, if you are located in the USA and reside in one of the following states: CA, CO, CT, FL, GA, IL, KS, MA, MD, ME, NJ, NC, NY, OR, TN, TX, VA, and WA. We have physical offices in Austin, TX and Tampa, FL, if you prefer a hybrid option. We hire the best data engineers, but experience in our stack can't hurt: our data platform is built on Kafka, Spark, Airflow, Iceberg, and Databricks; supporting large-scale distributed workloads across hybrid streaming and batch ecosystems. Knowing lakehouse architecture patterns, distributed query engines, and scalable pipeline design will set you up for success.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, Information Technology, or equivalent work experience preferred.
10+ years of experience in data engineering with a strong focus on data platform and distributed systems.
Hands-on experience building and managing lakehouse architectures, including Medallion (Bronze/Silver/Gold) layering patterns.
Deep expertise in Apache Kafka, Apache Spark, and Apache Airflow for both streaming and batch pipeline development.
Proficiency in open table formats — Iceberg, Delta Lake, or Hudi — with the ability to evaluate trade-offs and select the right format for the workload.
Experience with Databricks for large-scale data processing and analytics workloads.
Strong proficiency in Python and SQL.

Nice To Haves

Hands-on experience with Trino or Starburst for distributed query execution.
Familiarity with hybrid streaming/batch architectures and event-driven data systems.
Experience designing Gold-layer datasets optimized for business intelligence and self-serve analytics.

Responsibilities

Design and implement Medallion-layer data architectures (Bronze, Silver, Gold), building structured ingestion pipelines and curated data layers that serve downstream analytics and data science workloads.
Build and maintain scalable streaming and batch data pipelines using Kafka, Spark, and Airflow, supporting reliable and low-latency data movement across the platform.
Own and manage open table formats including Iceberg, Delta, and Hudi — selecting the right format for the workload and maintaining performance and reliability at scale.
Work with Trino/Starburst and Databricks-based environments to optimize large-scale analytics queries and support platform consumers.
Monitor pipeline health, troubleshoot data quality and performance issues, and continuously improve the reliability and efficiency of the data platform.
Partner closely with data scientists, analysts, and product teams to understand data requirements and deliver platform solutions that enable data-driven decision-making.
Other duties as needed.