AWS Data Engineer-C2C contract hiring- Malvern, Pennsylvania

Tech Mirrors; Malvern (Chester County); On-site; USD 120,000 - 150,000; Full time

Job summary

Tech Mirrors is seeking an experienced AWS Data Engineer in Malvern, Pennsylvania. The role involves building and maintaining event-driven data pipelines utilizing AWS services, developing ETL/ELT workflows in Python and PySpark, and ensuring data quality and security practices.

The ideal candidate has over 8 years of experience, with at least 5 years focused on Data Engineering. Strong expertise in AWS and hands-on experience with event-driven architecture are essential.

Qualifications

• 8+ years of overall experience.
• 5+ years of experience in Data Engineering.
• Strong expertise in Python and PySpark.
• Advanced AWS experience including S3, Glue, EMR.
• Experience with CI/CD and infrastructure as code.

Responsibilities

• Build and maintain event-driven data pipelines using AWS services.
• Develop ETL/ELT workflows using Python and PySpark.
• Implement and optimize Spark-based data transformations.
• Design data lake and warehouse structures using AWS services.
• Ensure high standards of data quality and observability.

Skills

Python

PySpark

AWS (S3, Glue, EMR, Lambda)

SQL

Event-driven architecture

CI/CD

Airflow

Tools

Terraform

CloudFormation

Job description

AWS Data Engineer

Malvern, Pennsylvania (Onsite) – Contract

Responsibilities

• Build and maintain event‑driven data pipelines using AWS services such as Kinesis, MSK/Kafka, Lambda, Step Functions, SQS/SNS, and Glue/EMR.
• Develop ETL/ELT workflows using Python and PySpark, ensuring performance, scalability, and cost efficiency.
• Implement and optimize Spark‑based data transformations, partitioning strategies, and data processing frameworks.
• Design and manage data lake and warehouse structures using S3, Glue Catalog, Athena, and/or Redshift.
• Build streaming solutions with checkpointing, stateful transformations, idempotency, and schema evolution.
• Ensure high standards of data quality, observability, monitoring, and alerting via CloudWatch, Datadog, etc.
• Implement data security best practices including IAM, encryption (KMS), networking, and governance.
• Create reusable frameworks, internal libraries, and CI/CD pipelines for automated deployments.
• Collaborate with data scientists, analysts, and business teams to deliver well‑modeled, reliable datasets.
• Lead design reviews, mentor junior engineers, and contribute to engineering best practices.

Required Qualifications

• Overall 8+ years of experience.
• 5+ years of professional experience in Data Engineering.
• Experience with Glue jobs and Lambda.
• Experience with Java is an advantage.
• Strong expertise in Python and PySpark for large‑scale data processing.
• Advanced hands‑on experience with AWS (S3, Glue, EMR, Lambda, Step Functions, Kinesis/MSK, DynamoDB, Athena, Redshift).
• Deep experience building event‑driven and streaming data pipelines.
• Strong SQL experience for analytical and ETL workloads.
• Hands‑on experience with workflow orchestration tools such as Airflow or Step Functions.
• Experience with CI/CD, Git, and Infrastructure‑as‑Code (Terraform or CloudFormation).
• Strong understanding of distributed systems, Spark performance tuning, data modeling, and cloud cost optimization.
• Knowledge of data security, encryption, networking, and compliance best practices in cloud environments.