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# Data Engineer - AWS & PySpark

- **Company:** Cliff Services Inc
- **Location:** Dallas, TX, United States
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Amazon S3, Big Data, Data as a Services, Extract Transform Load (ETL), Data Transformation, Data Systems, Distributed Computing Environment, Python (Programming Language), Cloud Services, Standard Sql, Data Processing, Cloud Platform System, Pyspark, Data Pipelines
- **Published:** August 25, 2026
- **Apply:** https://www.dice.com/job-detail/a65d4e0a-92f5-44f4-8d18-3734d643ffa9

## About the Role

We are looking for an experienced Data Engineer with strong hands-on expertise in AWS and PySpark. The ideal candidate must have prior professional experience working with Banking domain and be capable of developing scalable data pipelines and data processing solutions in a cloud environment., * Strong hands-on experience with PySpark.

 * Strong experience with AWS cloud services.
 * Experience developing ETL/data pipelines and processing large datasets.
 * Strong Python and SQL skills.
 * Experience with data transformation, integration, and data quality.
 * Mandatory: Prior Capital One project/client experience.
 * Strong communication and problem-solving skills.

Preferred

 * Experience with AWS data services such as S3, Glue, EMR, Lambda, Redshift, or similar.
 * Experience with distributed data processing and cloud-based data platforms.
 * Financial services/banking domain experience.

## Description

* Design, develop, and maintain scalable data pipelines using PySpark and AWS.
 * Develop and optimize large-scale data processing and ETL workflows.
 * Work with AWS cloud services to build reliable and high-performance data solutions.
 * Perform data transformation, cleansing, validation, and integration.
 * Optimize PySpark jobs for performance, scalability, and cost efficiency.
 * Collaborate with data architects, analysts, developers, and business stakeholders.
 * Troubleshoot data pipeline issues and ensure data quality and reliability.
 * Follow engineering best practices for code development, testing, deployment, and documentation.


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