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Senior Data Engineer – Python, PySpark & AWS

SCI SOLUTIONS GLOBAL Plano, Texas, United States · $125K/yr

IT Services and IT Consulting · 11-50 employees

Yesterday
python Senior (5-10 yrs) Contractor United States
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About the role

Develop, test, and maintain scalable ETL/ELT data pipelines using Python and PySpark. Build and support big-data processing solutions on AWS while orchestrating workflows using tools like Airflow.

What they look for

Python PySpark AWS ETL ELT S3 EMR Lambda Terraform REST APIs Kafka MQ Messaging Cassandra Airflow Control-M Java

Requirements

Requires strong hands-on experience with Python, PySpark, and AWS services such as S3, EMR, and Lambda. Candidates must have at least 5 years of experience and be authorized to work in the US without visa sponsorship.

Full description

Senior Data Engineer – Python, PySpark & AWS

Location: Plano, TX

Relocation : Open

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

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

Role Overview

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.

Key Responsibilities

  • 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.

Required Skills

  • 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.

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