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# Databricks Engineer

- **Company:** Voto Consulting LLC
- **Location:** Charlotte, NC, United States
- **Experience:** Experienced
- **Contract:** Temporary contract
- **Skills:** Business Analytics Applications, Microsoft Azure, Big Data, Cloud Database, Continuous Integration, Information Engineering, Data Governance, Extract Transform Load (ETL), DevOps, Identity and Access Management, Python (Programming Language), NoSQL, Azure Data Lake, Scala (Programming Language), Data Processing, Data Storage Technologies, Azure Data Factory, Sql Optimization, Apache Spark, Git, Build Management, Data Lakes, Pyspark, Infrastructure Automation Frameworks, Information Technology, Terraform, Data Pipelines, Databricks
- **Published:** August 26, 2026
- **Apply:** https://www.dice.com/job-detail/a4955830-5b1e-4c03-bca9-bdc6cf139566

## About the Role

* Experience: 3 to 7+ years of total experience in data engineering or cloud-based data platform development.
 * Core Technologies: Hands-on proficiency in Azure Databricks, Apache Spark, PySpark, and Azure Data Factory (ADF).
 * Languages: Advanced SQL and solid programming skills in Python or Scala.
 * Data Concepts: Strong grasp of Delta Lake, relational/NoSQL data storage, data modeling, and data quality standards.
 * Education: Bachelor's degree in Computer Science, Engineering, or a related quantitative field (often preferred)

## Description

Databricks Engineer to design, build, and maintain scalable data pipelines, lakehouse architectures, and analytics solutions using Microsoft Azure and the Databricks platform., * Pipeline Development: Design and build Extract, Transform, Load (ETL) and ELT data pipelines using Azure Data Factory (ADF) and Azure Databricks

 * Big Data Processing: Write optimized data processing code using Apache Spark, PySpark, Python, Scala, and advanced SQL.
 * Storage & Architecture: Implement and manage data lakes using Azure Data Lake Storage (ADLS Gen2) and Delta Lake / lakehouse patterns.
 * Governance & Security: Configure data governance, lineage, and access controls using Databricks Unity Catalog and Azure IAM.
 * Optimization & Operations: Monitor, troubleshoot, and tune Spark jobs and data pipelines for performance, reliability, and cost-efficiency.
 * CI/CD & DevOps: Support deployment processes utilizing Azure DevOps, Git version control, and infrastructure-as-code tools like Terraform.


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