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# Senior Data Engineer - Python, PySpark & AWS

- **Company:** Sci Solutions Global
- **Location:** Plano, TX, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Airflow, Amazon Web Services, Amazon S3, Big Data, Cloud Computing, Data Integration, Extract Transform Load (ETL), Distributed Computing Environment, Python (Programming Language), Machine Learning, Operational Databases, Data Storage Management, Pyspark, Infrastructure Automation Frameworks, Cassandra, Apache Kafka, Restful APIs, Terraform, Data Pipelines, Databricks, Control M
- **Published:** November 5, 2026
- **Apply:** https://www.thejobnetwork.com/job/e64896eb-449d-4a58-9e18-d627caffac22/senior-data-engineer-python-pyspark-aws

## About the Role

* Strong hands-on Python and PySpark experience.
 * Experience with big-data processing and production data pipelines.
 * AWS experience with S3, EMR, and Lambda.
 * Working knowledge of Terraform.
 * Familiarity with Kafka, MQ messaging, REST APIs, Java, and Cassandra.
 * Experience with Airflow, Control-M, or other workflow scheduling tools.

Preferred: Databricks experience and exposure to machine-learning workflows.

## Description

We are seeking a hands-on Senior Data Engineer with strong Python, PySpark, and AWS experience to develop and maintain scalable data pipelines and distributed data processing solutions. The ideal candidate will have experience supporting production data engineering workloads, cloud infrastructure, and data orchestration., * Develop, test, and maintain ETL/ELT data pipelines using Python and PySpark.

 * Build and support big-data processing solutions on AWS using S3, EMR, and Lambda.
 * Implement infrastructure automation using Terraform.
 * Develop data integrations using REST APIs, Kafka, and MQ messaging.
 * Support data storage and retrieval using Cassandra.
 * Orchestrate and monitor workflows using Airflow, Control-M, and native schedulers.
 * Troubleshoot pipeline failures and optimize performance, reliability, and data quality.