Key Responsibilities

Design, develop, and maintain scalable and high-performance data pipelines using Python and PySpark.
Build, deploy, and manage ETL/ELT workflows using AWS Glue and AWS Step Functions.
Develop serverless applications and automation solutions using AWS Lambda.
Write clean, efficient, maintainable, and reusable code following software engineering best practices.
Provision and manage cloud infrastructure using Terraform and Infrastructure as Code (IaC) principles.
Design, implement, and maintain CI/CD pipelines to automate code deployment, testing, and infrastructure changes.
Monitor, troubleshoot, and optimize data pipelines to ensure performance, reliability, and cost efficiency.
Implement logging, monitoring, and alerting solutions using AWS CloudWatch and other observability tools.
Collaborate with business stakeholders, solution architects, and technology teams to understand requirements and deliver effective data solutions.
Support production deployments, incident resolution, root cause analysis, and continuous improvement initiatives.
Ensure all solutions adhere to security, compliance, DevOps, and coding standards.

Requirements

Bachelor's Degree in Computer Science, Information Technology, Software Engineering, Data Science, or a related discipline.
Minimum 5 years of experience in Data Engineering, with at least 3 years of hands-on experience working on AWS cloud platforms.
Hands-on experience with Python and PySpark for large-scale data processing and transformation.
Proven experience developing and managing ETL/ELT pipelines using AWS Glue.
Proficiency in workflow orchestration using AWS Step Functions.
Experience building serverless applications and integrations using AWS Lambda.
Hands-on experience with Terraform for Infrastructure as Code (IaC).
Experience implementing and managing CI/CD pipelines using tools such as GitHub Actions, GitLab CI/CD, Jenkins, Azure DevOps, or similar platforms.
Good understanding of AWS services, including S3, IAM, CloudWatch, and data lake architectures.
Experience in monitoring, troubleshooting, and optimizing cloud-based data solutions.
Experience working with large-scale data platforms and distributed data processing environments.
Excellent communication and stakeholder management skills, with the ability to work effectively across technical and business teams.
AWS certifications such as AWS Certified Data Engineer, AWS Certified Solutions Architect, or AWS Certified Developer are good to have.

Jireli Gem Mejia Cabria EA License No.: 02C3423 Personnel Registration No.: R1434374

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Data Engineer (AWS, PySpark)