Databricks Engineer

General Dynamics

Confirmed live today High trust
Remote Hybrid

Quick summary

Work type
Remote
Location
Silver Spring, MDGaithersburg, MD
Salary
$140,250–$189,750 / yr
Posted
2 days ago
Freshness
Confirmed live today

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $170k
This role $165k
$115k most similar roles pay here $222k

This role pays more than 53% of similar roles. Most pay $129,126–$211,200 — the shaded band above. At the midpoint, this role pays about $165k versus about $170k for comparable roles.

Based on 240 similar postings.

Employer

About General Dynamics

General Dynamics is a global aerospace and defense company offering a broad portfolio of products and services in business aviation, ship construction, land combat vehicles, and information technology. It serves customers in the U.S. government, allied governments, and a diverse array of commercial markets.

General Dynamics currently has 1231 open roles on FindRole.

Listed pay typically runs $120,350–$150,385 across 1058 roles with salary data.

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At a glance

TL;DR · Databricks Engineer

The Databricks Engineer joins a team focused on building and operating modern data solutions for the NIA Data Enclave. In this role, you will design, develop, and optimize scalable ETL/ELT pipelines to provide researchers and analysts with secure access to sensitive federal and non-federal datasets. You will build and maintain Databricks notebooks, jobs, and workflows while managing high-volume analytical workloads through Spark optimization, partitioning, and caching. The technical stack includes Databricks, PySpark, SQL, Delta Lake, and Databricks Lakeflow. You will also utilize Git for CI/CD processes, manage cloud storage across AWS S3, Azure Data Lake Storage, or Google Cloud Storage, and implement data governance via the Unity Catalog. This position solves critical problems regarding data quality, security, and reliability within a secure, role-based environment to transform complex information into accessible analytical resources.

What you'll do

  • Design, build, and optimize scalable ETL/ELT pipelines using Databricks, PySpark, SQL, and Delta Lake.
  • Develop and maintain Databricks notebooks, jobs, and workflows to support high-volume analytical workloads.
  • Implement automated testing, data quality checks, monitoring, logging, and operational processes for data integrity.
  • Optimize Spark workloads through effective partitioning, caching, join management, and other performance-tuning techniques.
  • Support CI/CD and infrastructure automation for Databricks workloads using Git and tools like Azure DevOps or GitHub Actions.
  • Configure and optimize Databricks compute resources, including clusters, runtimes, and job execution settings.
  • Manage data governance and access controls within secure, role-based cloud environments.
  • Troubleshoot production issues and perform root-cause analysis to improve the reliability of data services.

What we're looking for

  • Bachelor's degree in computer science, software engineering, data engineering, or a related technical field.
  • 7+ years of related experience.
  • 5+ years of data engineering experience with significant hands-on experience with Databricks.
  • Strong experience with PySpark, SQL, Apache Spark, Delta Lake, and Databricks.
  • Experience developing production-grade data pipelines using Git and CI/CD practices.
  • Experience working with cloud-based platforms such as AWS S3, Azure Data Lake Storage, or Google Cloud Storage.
  • Understanding of distributed data processing, data modeling, and cloud security concepts like role-based access control.
  • Experience with Databricks Unity Catalog, multi-cloud environments, or infrastructure-as-code tools like Terraform (preferred).

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