Data Engineer, Databricks

Vital Tech Solutions

. Design, build, and maintain batch and streaming data pipelines using PySpark, SQL, Databricks Workflows, and Delta Live Tables .

Posted 9/22/2026full-timeRemote • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and maintaining data pipelines using PySpark, SQL, and Databricks, with a strong focus on data modeling and architecture principles. Proficient in integrating diverse data sources and optimizing performance in data engineering environments.

Highest-signal resume keywords

PySparkSQLDatabricksData ModelingData Engineering

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data Pipeline DevelopmentBatch ProcessingStreaming Data ProcessingData Quality ChecksData ValidationAPI DevelopmentData IntegrationMedallion ArchitecturePythonGit

Soft Skills

CollaborationCommunication

Tools & Technologies

Databricks WorkflowsDelta Live TablesKafkaKinesisDatabricks Auto LoaderDatabricks Unity Catalog

Certifications & Qualifications

Active Secret Security Clearance

Industry Keywords

Data EngineeringData ArchitectureCI/CDU.S. CitizenshipBachelor's Degree

Tech Stack

Tools & technologies

KafkaPySparkPythonSparkSQLUnity

About the role

Key responsibilities & impact

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
Develop scalable ingestion frameworks for structured, semi-structured, and unstructured data
Integrate data from files, databases, APIs, Kafka, Kinesis, and Databricks Auto Loader
Design dimensional and domain-specific data models
Build and consume APIs for downstream system integration
Optimize Spark workloads for performance and cost through partitioning, caching, cluster sizing, and related techniques
Develop 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

What you’ll need

U.S. citizenship
Must reside in the United States
Active Secret security clearance or higher 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 databases, APIs, files, and streaming platforms
Bachelor's degree in Computer Science, Engineering, Information Technology, or a related discipline (preferred qualification)

Benefits

Comp & perks

Remote work opportunity
Opportunity to support federal government programs