Senior Data Engineer — Python, PySpark & AWS

SCI SOLUTIONS GLOBAL; Plano (TX); Presencial; USD 120.000 - 160.000; Jornada completa

Descripción de la vacante

SCI SOLUTIONS GLOBAL in Plano, TX is 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 support production data engineering workloads, cloud infrastructure, and data orchestration, with experience in Terraform, Kafka, REST APIs, and Cassandra, and be familiar with Airflow or Control-M for workflow scheduling.

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.
• Familiarity with Kafka, MQ messaging, REST APIs, Java, and Cassandra.
• Experience with Airflow, Control-M, or other workflow schedulingtools.

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

Big data processing

AWS

S3/EMR/Lambda

REST APIs

Kafka

MQ messaging

Java

Cassandra

Airflow

Control-M

Herramientas

Terraform

Airflow

Control-M

Descripción del empleo

SCI SOLUTIONS GLOBAL in Plano, TX is 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 support production data engineering workloads, cloud infrastructure, and data orchestration, with experience in Terraform, Kafka, REST APIs, and Cassandra, and be familiar with Airflow or Control-M for workflow scheduling.