Databricks Data Engineer

Zohorecruit; Washington (District of Columbia); Remote; USD 120,000 - 160,000; Full time

Job summary

Vital Tech Solutions is seeking a Databricks Data Engineer for a federal technology initiative. This remote role requires an active Secret clearance and US citizenship; work will involve building batch and streaming pipelines in Databricks with PySpark and SQL, plus data modeling and ingestion frameworks.

You will collaborate with engineers and federal program stakeholders throughout the development lifecycle, implementing Delta Live Tables, Unity Catalog permissions, and scalable architectures

Qualifications

• Active Secret security clearance or higher required.
• 5+ years professional data engineering experience.
• 2+ years hands-on Databricks experience.
• Strong PySpark and SQL production-level experience.
• Experience developing both batch and streaming data pipelines.
• Strong data modeling and modern data architecture knowledge.
• Python proficiency and Git-based development experience.
• Familiarity with Unity Catalog permissions and ingestion from multiple sources.

Responsibilities

• Design, build, and maintain batch and streaming data pipelines with PySpark, SQL, Databricks Workflows, and Delta Live Tables.
• Implement Medallion Architecture across bronze, silver, and gold data layers.
• Develop scalable ingestion frameworks for structured, semi-structured, and unstructured data.
• Integrate data from databases, APIs, files, and streaming sources (Kafka, Kinesis, Databricks Auto Loader).
• Design dimensional and domain-specific data models for analytics and downstream apps.
• Build and consume APIs for integration with downstream systems.
• Optimize Spark workloads for performance and cost via partitioning and caching.
• Maintain data quality checks, validation, and pipeline monitoring.
• Document data flows, lineage, architecture, and integration points.
• Collaborate with engineering, platform, architecture, and federal stakeholders throughout the lifecycle.

Skills

Databricks

PySpark

SQL

Python

Data Modeling

CI/CD

Git

Data Pipelines

Cloud Platforms

Education

Bachelor's degree in Computer Science / Engineering / IT

Tools

Databricks Unity Catalog

Databricks Workflows

Delta Live Tables

Kafka

Kinesis

Databricks Auto Loader

Git-based CI/CD

Job description

Security Clearance: Active Secret or higher REQUIRED

Our client, a growing technology services organization supporting federal government programs, is seeking an experienced Databricks Data Engineer to support a federal technology initiative.

This is a remote opportunity available to U.S. citizens residing in the United States . Candidates must currently hold an ACTIVE Secret security clearance or higher . Candidates without an active Secret-level clearance cannot be considered.

The ideal candidate will bring strong hands-on data engineering experience within Databricks, including development of production-grade batch and streaming pipelines, PySpark and SQL transformations, data modeling, ingestion frameworks, and modern data architecture practices.

Responsibilities

• Design, build, and maintain batch and streaming data pipelines using PySpark, SQL, Databricks Workflows, and Delta Live Tables.
  
• Implement Medallion Architecture across bronze, silver, and gold data layers to support data quality, transformation, and consumption.
  
• Develop scalable ingestion frameworks for structured, semi-structured, and unstructured data.
  
• Integrate data from files, databases, APIs, and streaming sources such as Kafka, Kinesis, and Databricks Auto Loader.
  
• Design dimensional and domain-specific data models supporting analytics and downstream applications.
  
• Build and consume APIs for integration with downstream systems.
  
• Optimize Spark workloads for performance and cost through partitioning, caching, cluster sizing, and related techniques.
  
• Develop and implement data quality checks, validation processes, and pipeline monitoring.
  
• Maintain documentation covering data flows, lineage, architecture, and integration points.
  
• Collaborate with engineering, platform, architecture, and federal program stakeholders throughout the development lifecycle.
  

Requirements

• Active Secret security clearance or higher is required.
  
• 5+ years of professional data engineering experience.
  
• 2+ years of hands-on Databricks experience.
  
• Strong production-level experience with PySpark and SQL .
  
• Experience developing both batch and streaming data pipelines.
  
• Strong understanding of data modeling and modern data architecture principles.
  
• Proficiency with Python.
  
• Experience working within Git-based development and CI/CD environments.
  
• Familiarity with Databricks Unity Catalog, including catalogs, schemas, and permissions from a data engineering perspective.
  
• Experience integrating data from multiple source types, including databases, APIs, files, and streaming platforms.
  

Preferred Qualifications

• Experience with Databricks Delta Live Tables.
  
• Experience with Databricks Workflows.
  
• Experience with Kafka, Kinesis, or similar streaming technologies.
  
• Experience working within federal, regulated, or security-sensitive environments.
  
• Bachelor's degree in Computer Science, Engineering, Information Technology, or a related discipline.