Data Engineer, Databricks

Job not on LinkedIn

🔥 24 minutes ago

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 12%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Vital Tech Solutions

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2017

💼 Consulting

🏥 Healthcare

📦 Logistics

Consulting • Healthcare • Logistics

Vital Tech Solutions is a WBENC-certified technology consulting and workforce solutions firm that delivers enterprise application management, project management outsourcing, IT and engineering consulting, and human capital/recruiting services to Fortune 2000 clients. The company emphasizes Agile methodologies, operational efficiency, and technology-agnostic product and engineering support across cloud, infrastructure, software development, QA, and manufacturing/product engineering disciplines. Vital Tech serves multiple industries including automotive, manufacturing, banking and financial services, government, healthcare, energy, and supply chain, positioning itself as a B2B partner for enterprise digital transformation and talent acquisition.

📋 Description

• 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

• 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

• Remote work opportunity • Opportunity to support federal government programs