Themesoft Inc.
Senior AWS Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior AWS Data Engineer located in Malvern, PA, with a contract length of "unknown." The pay rate is "unknown." Key skills include AWS services, Python, PySpark, ETL workflows, and data security practices. Requires 8+ years of experience, including 5+ in Data Engineering.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
May 16, 2026
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Malvern, PA
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🧠 - Skills detailed
#Compliance #Lambda (AWS Lambda) #Data Lake #Datasets #Libraries #Cloud #AWS S3 (Amazon Simple Storage Service) #Redshift #Data Transformations #Data Quality #Spark (Apache Spark) #SQL (Structured Query Language) #Deployment #Data Processing #Data Modeling #Datadog #Kafka (Apache Kafka) #Scala #Data Pipeline #Airflow #Terraform #Observability #Java #DynamoDB #Data Engineering #Data Science #GIT #Data Security #PySpark #Athena #Monitoring #AWS (Amazon Web Services) #IAM (Identity and Access Management) #S3 (Amazon Simple Storage Service) #Python #Security #SQS (Simple Queue Service) #SNS (Simple Notification Service) #"ETL (Extract #Transform #Load)"
Role description
Location: Malvern, PA
Role Name - Senior Data Engineer
ROLE\_DESCRIPTION -
• 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 (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+ yrs of experience
• 5+ years of professional experience in Data Engineering
• Must have an experience on Gule jobs and Lambda,
• Experience of working on 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
Location: Malvern, PA
Role Name - Senior Data Engineer
ROLE\_DESCRIPTION -
• 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 (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+ yrs of experience
• 5+ years of professional experience in Data Engineering
• Must have an experience on Gule jobs and Lambda,
• Experience of working on 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
