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# Databricks Engineer AWS_Dallas, TX-Locals

- **Company:** Keylent Inc.
- **Location:** Dallas, TX, United States
- **Experience:** Expert
- **Contract:** Contract
- **Skills:** Amazon Web Services, Amazon S3, Continuous Integration, Data Validation, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Transformation, Data Warehousing, Database Queries, Distributed Computing Environment, Python (Programming Language), Performance Tuning, SQL Databases, Apache Spark, Git, Data Lakes, Pyspark, AWS Glue, Apache Kafka, Stream Processing, Data Pipelines, Amazon Redshift, Databricks
- **Published:** October 27, 2026
- **Apply:** https://www.dice.com/job-detail/a77321fe-30f6-411d-ac2a-ffd9505c2aef

## About the Role

* 10+ years of strong hands-on experience with AWS services
 * Strong expertise in Python and PySpark development
 * Strong hands-on experience with Databricks
 * Experience developing Databricks notebooks, workflows, and ETL pipelines
 * Strong knowledge of Apache Spark / PySpark and distributed data processing
 * Experience with Databricks Delta Lake / Delta tables
 * Hands-on experience with Databricks SQL and data transformation
 * Experience building and optimizing Databricks ETL/data engineering pipelines
 * Experience with AWS Glue and ETL process development
 * Strong SQL skills for data transformation, analysis, and optimization
 * Hands-on experience with Kafka for real-time data processing
 * Experience with Amazon Redshift
 * Experience integrating Databricks with AWS services, including S3, Glue, and Redshift
 * Knowledge of Git pipelines and CI/CD processes
 * Experience deploying and managing Databricks jobs/workflows through CI/CD
 * Strong understanding of ETL workflows and data integration
 * Experience in ETL testing, validation, and data quality checks
 * Expertise in ETL automation frameworks and process optimization
 * Experience with data pipeline performance tuning and Spark optimization
 * Strong understanding of batch and real-time data processing
 * Experience troubleshooting and optimizing Spark/Databricks jobs
 * Strong knowledge of data lake / data warehouse concepts
 * Experience working with large-volume datasets and distributed processing

Must Have: AWS + Python + PySpark + Databricks + AWS Glue + SQL + Kafka + Redshift + ETL