AWS Data Engineer

Staffxpert Llc
Chicago, IL, United States
3 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Job source

Tech stack

Amazon Web Services Amazon S3 Automation of Tests Big Data Code Review Continuous Integration Data Governance Extract Transform Load (ETL) Data Security Relational Databases DevOps Python (Programming Language)
+18 more
PostgreSQL Operational Databases Oracle (Applications) Performance Tuning Scrum Methodology Cloud Services Standard Sql SQL Databases Software Organization Apache Spark Git Pyspark Infrastructure Automation Frameworks AWS Glue AWS Data Analytics Amazon Simple Queue Service (SQS) Software Version Control Data Pipelines

Job description

STAFFXPERT LLC is seeking an AWS Data Engineer on behalf of our client in multiple U.S. locations. This role is responsible for designing, developing, and optimizing scalable cloud-based data pipelines and ETL solutions within an AWS ecosystem. The ideal candidate will bring strong expertise in PySpark, Python, AWS Glue, and relational databases, along with a passion for building high-performance, reliable, and secure data platforms., * Design, build, and maintain scalable ETL and data processing pipelines using Python, PySpark, and AWS Glue

  • Develop cloud-native data solutions leveraging AWS services such as S3, Lambda, Step Functions, ECS, SNS, and SQS
  • Optimize Spark jobs, SQL queries, and data workflows for performance and scalability
  • Develop and maintain PL/SQL scripts and database solutions in Oracle, PostgreSQL, or similar relational databases
  • Implement software engineering best practices including version control, automated testing, CI/CD, and code reviews
  • Monitor production data environments, troubleshoot issues, and perform root cause analysis
  • Collaborate with cross-functional teams including architects, developers, analysts, and business stakeholders
  • Maintain technical documentation and support operational excellence initiatives

Requirements

  • Strong hands-on experience building production-grade data pipelines using Python and PySpark
  • Expertise with AWS cloud services including S3, Glue, Lambda, Step Functions, ECS, SNS, and SQS
  • Strong SQL and PL/SQL development experience with relational databases such as Oracle or PostgreSQL
  • Experience with Spark performance tuning and large-scale data processing
  • Solid understanding of software development best practices including Git, testing, and CI/CD pipelines
  • Experience with monitoring, observability, alerting, and production support processes
  • Strong analytical, troubleshooting, and problem-solving skills
  • Excellent verbal and written communication skills

Preferred Qualifications

  • Experience working with enterprise-scale cloud data platforms
  • Familiarity with DevOps practices and Infrastructure-as-Code tools
  • Knowledge of data governance, security, and compliance standards
  • Experience working in Agile/Scrum environments

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