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# Lead Databricks Developer

- **Company:** I8IS INC.
- **Location:** Wilmington, DE, United States
- **Experience:** Expert
- **Salary:** $104,000.0 - $114,400.0
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Airflow, Amazon Web Services, Business Analytics Applications, Microsoft Azure, Cloud Database, Continuous Integration, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Transformation, Apache Hive, Python (Programming Language), Standard Sql, SQL Databases, Data Streaming, Data Logging, Data Processing, Azure Data Factory, Apache Spark, Caching, Git, Data Lakes, Pyspark, Deployment Automation, Apache Kafka, Machine Learning Operations, Stream Processing, Data Pipelines, Databricks
- **Published:** July 31, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=605d275d038f102d

## About the Role

* Strong hands-on experience with Databricks
 * Strong Python programming skills
 * Strong in communication and proactive.
 * Expertise in Apache Spark, PySpark, and Spark SQL- Strong SQL and data transformation skills
 * Experience with Delta Lake and lakehouse concepts- Knowledge of ETL/ELT and data pipeline design
 * Experience with AWS, Azure, or GCP- Familiarity with Git, CI/CD, and Agile practices
 * Good problem-solving and communication skills

Preferred Skills:-

 * Experience with Airflow, Azure Data Factory, or Databricks Workflows
 * Knowledge of Kafka or streaming frameworks
 * Experience with MLflow or analytics platforms
 * Understanding of data governance and security best practices

## Description

Summary: We are looking for a Lead Databricks Developer with strong experience in Python and Apache Spark to design, develop, and optimize scalable data pipelines and cloud-based data solutions. The ideal candidate will have hands-on expertise in Databricks, PySpark, SQL, and modern data engineering practices., Design, develop, and maintain ETL/ELT pipelines using Databricks and PySpark- Build scalable batch and real-time data processing solutions using Apache Spark- Develop data transformation workflows using Python, PySpark, and Spark SQL- Implement Delta Lake solutions and optimize data processing performance- Create and manage Databricks notebooks, jobs, and workflows- Ensure data quality, validation, logging, and exception handling- Optimize Spark performance using partitioning, caching, and tuning techniques- Collaborate with cross-functional teams to gather requirements and deliver solutions- Support CI/CD, deployment automation, and production releases- Troubleshoot and resolve issues in data pipelines and platform processes


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