Senior Data Engineer

Lorgan Tech Solutions, LLC (LorganTech) is hiring a Senior Data Engineer to help design, build, and optimize enterprise data solutions in a remote environment. This role centers on production-grade ETL/ELT, Delta Lake patterns, and governed data access using Unity Catalog.

You will work across the full lifecycle of data delivery, from reliable batch and streaming pipelines to curated datasets for reporting and downstream applications. The position combines hands-on Databricks and PySpark development with cloud platform experience and engineering practices like CI/CD and deployment automation.

Role Responsibilities

• Develop and maintain scalable ETL/ELT pipelines using Databricks, PySpark, and SQL.
• Implement Bronze, Silver, and Gold layers using Delta Lake and medallion architecture.
• Build reliable batch and streaming pipelines with incremental processing, deduplication, and recovery capabilities.
• Design data models and curated datasets supporting reporting, analytics, and downstream applications.
• Optimize Spark workloads including cluster configurations and query performance.
• Implement data quality checks along with monitoring, logging, and error handling.
• Manage data access, governance, and lineage using Unity Catalog.
• Automate deployments using Git and CI/CD practices.
• Collaborate with architects, analysts, and business stakeholders.
• Mentor engineers and contribute to technical design and code reviews.

Required Qualifications

• 10+ years of professional Data Engineering experience.
• Strong hands-on experience with Databricks, Apache Spark, PySpark, and SQL.
• Proficiency in Python and distributed data processing.
• Experience with Delta Lake, medallion architecture, and data modeling.
• Experience with at least one cloud platform: Azure, AWS, or GCP.
• Knowledge of orchestration using Databricks Workflows, Airflow, or Azure Data Factory.
• Experience implementing incremental loads, CDC, and data validation.
• Familiarity with Unity Catalog, security, and data governance.
• Experience with Git, CI/CD, and production troubleshooting.
• Strong communication, problem-solving, and collaboration skills.

Technologies

• Databricks
• PySpark
• SQL
• Apache Spark
• Python
• Delta Lake
• Unity Catalog
• Git
• CI/CD
• Databricks Workflows
• Airflow
• Azure Data Factory
• Azure
• AWS
• GCP

Preferred Qualifications

• Experience with Auto Loader, Structured Streaming, or declarative pipelines.
• Familiarity with dbt, Terraform, and infrastructure automation.
• Databricks certification.

Compensation and Location

• Location: Remote
• Rate: USD $60.00 - $65.00 per hour

How to Apply

Send your resume to [email protected] with the subject line: Senior Data Engineer – Databricks. Include your current location, availability, and a brief summary of your Databricks experience.