Senior Data Engineer – Python, PySpark & AWS

SCI SOLUTIONS GLOBAL; Plano (TX); Presencial; USD 120.000 - 180.000; Jornada completa

Descripción de la vacante

SCI SOLUTIONS GLOBAL in Plano, Texas, is seeking a hands-on Senior Data Engineer who can build and maintain scalable ETL/ELT data pipelines using Python, PySpark, and AWS. You will support production workloads, cloud infrastructure, and data orchestration in a fast-paced environment.

Responsibilities include developing end-to-end pipelines with Python/PySpark, building data integrations via REST APIs, Kafka, and MQ, storing data in Cassandra, and orchestrating workflows with Airflow or Control-M.

Formación

• 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.

Responsabilidades

• 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.
• 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.

Conocimientos

Python

PySpark

AWS

Terraform

Kafka/MQ

REST APIs

Cassandra

Airflow/Control-M

Descripción del empleo

Plano, United States | Posted on 11/02/2026

Relocation: Open

Open for W2 only- No c2c/1099 or third party resumes

Due to the nature of the roles client is onlyaccepting USC/GC /GC EAD only no other visas accepted .

RoleOverview

We areseeking a hands-on Senior Data Engineer with strong Python, PySpark, and AWSexperience to develop and maintain scalable data pipelines and distributed dataprocessing solutions. The ideal candidate will have experience supportingproduction data engineering workloads, cloud infrastructure, and dataorchestration.

KeyResponsibilities

• Develop, test, and maintain ETL/ELT data pipelines using Python andPySpark.
• Build and support big-data processing solutions on AWS using S3,EMR, and Lambda.
• 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, andnative schedulers.
• Troubleshoot pipeline failures and optimize performance,reliability, and data quality.

RequiredSkills

• 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, andCassandra.
• Experience with Airflow, Control-M, or other workflow schedulingtools.

Preferred:

Databricks experience and exposureto machine-learning workflows.