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Python AWS Spark Engineer, Plano, TX (Hybrid)

MetaRPOPlano, TX🇺🇸United StatesPosted Oct 6, 2026

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
Plano, TX, United States
Posted
3 days ago

Job Description

Python AWS Spark Engineer
Location: Plano, TX
Duration: Long-Term

Job Summary

Seeking an experienced Python AWS Spark Engineer to join the team in Plano, TX. The ideal candidate will have strong hands-on experience with Python, Apache Spark/PySpark, AWS cloud services, and data engineering. This role will focus on developing scalable data processing solutions, building cloud-based data pipelines, and supporting enterprise data platforms.

Key Responsibilities

  • Design, develop, and maintain scalable data pipelines using Python and Apache Spark/PySpark.
  • Develop high-performance ETL/ELT workflows for large-volume datasets.
  • Build and deploy data processing solutions on AWS.
  • Work with AWS services such as S3, Glue, EMR, Lambda, Redshift, and CloudWatch.
  • Develop and optimize Spark jobs for performance, scalability, and reliability.
  • Perform data transformation, cleansing, validation, and integration across multiple data sources.
  • Write efficient Python and SQL code for data processing and analytics.
  • Troubleshoot production issues and perform root-cause analysis.
  • Implement data quality, monitoring, logging, and error-handling mechanisms.
  • Collaborate with data engineers, architects, application teams, and business stakeholders.
  • Participate in code reviews, unit testing, deployment, and production support.
  • Follow enterprise security, compliance, and development standards within the banking environment.

Required Skills

  • 7+ years of experience in software/data engineering.
  • Strong hands-on experience with Python.
  • Strong experience with Apache Spark / PySpark.
  • Strong experience with AWS cloud services.
  • Hands-on experience with AWS S3, Glue, EMR, Lambda, and/or Redshift.
  • Strong SQL skills and experience working with relational databases.
  • Experience developing large-scale ETL/ELT data pipelines.
  • Experience with data transformation and processing of large datasets.
  • Strong understanding of distributed computing and Spark architecture.
  • Experience with Git and CI/CD practices.
  • Excellent problem-solving and communication skills.

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