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# Databricks Data Engineer

- **Company:** Eliassen Group
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $150,000.0 - $154,000.0
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Amazon Web Services, Data Analysis, JIRA, Cloud Database, Continuous Integration, Data Validation, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Systems, DevOps, Python (Programming Language), PostgreSQL, Software Engineering, SQL Databases, Apache Spark, Git, Information Technology, Data Lineage, Data Pipelines, Docker, Jenkins, Databricks
- **Published:** November 7, 2026
- **Apply:** https://www.dice.com/job-detail/8f133a4c-d1d6-4c9e-aceb-21986aa520c0

## About the Role

* Five or more years of experience in data engineering or a related role.
 * Expert proficiency in Python, SQL, Databricks, and Spark.
 * Experience building cloud-based data pipelines in AWS.
 * Knowledge of data governance, security, privacy, and retention practices.
 * Strong communication, collaboration, and problem-solving skills.
 * Experience working in agile environments using tools such as Jira.
 * Proficiency with Git, Docker, and CI tools such as Jenkins.
 * Passion for data and continuous improvement.
 * Preferred: Ability to work independently and proactively.
 * Preferred: Experience optimizing ETL workflows in Databricks.
 * Preferred: Knowledge of data lineage and data quality practices.
 * Preferred: Experience supporting data science and machine learning solutions.
 * Preferred: Prior experience in the energy or utility industry.

Education Requirements:

 * Bachelor's degree in computer science, information technology, or a related field.
 * Preferred: Master's degree in a relevant STEM field.

## Description

* Design, develop, and maintain data pipelines, infrastructure, and systems using AWS, Python, Databricks, Spark, and PostgreSQL.
 * Collaborate with cross-functional teams to translate business requirements into technical solutions.
 * Provide technical guidance and mentorship to junior data engineers.
 * Develop and implement data engineering standards and best practices.
 * Monitor and troubleshoot data pipelines to ensure data quality, integrity, and availability.
 * Research industry trends and evaluate new data technologies.
 * Build and maintain data lakes to support analytics and business intelligence.
 * Manage the software development life cycle and DevOps activities.
 * Partner with data scientists and analysts to deliver effective data solutions.
 * Develop data validation and data analysis tools.