

JSR Tech Consulting
Senior AWS Data Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior AWS Data Engineer with a contract length of "unknown" and a pay rate of "unknown." It is located in Newark, NJ (Hybrid – 3 days onsite). Requires 8+ years of data engineering experience, AWS certifications, and proficiency in Python, SQL, and DevOps practices.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
-
🗓️ - Date
July 16, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
Hybrid
-
📄 - Contract
Unknown
-
🔒 - Security
Unknown
-
📍 - Location detailed
Newark, NJ
-
🧠 - Skills detailed
#Shell Scripting #SQL (Structured Query Language) #Groovy #Data Lineage #Databases #SNS (Simple Notification Service) #Data Catalog #"ETL (Extract #Transform #Load)" #Jira #Python #Aurora #Cloudbees #BitBucket #SonarQube #Data Warehouse #IAM (Identity and Access Management) #Informatica #Spark (Apache Spark) #Athena #Data Access #SQS (Simple Queue Service) #Data Ingestion #Data Marketplace #Deployment #API (Application Programming Interface) #Automated Testing #DMP (Data Management Platform) #DevOps #Airflow #EC2 #Security #Infrastructure as Code (IaC) #Agile #Scala #Scripting #RDS (Amazon Relational Database Service) #Redshift #Data Architecture #AWS (Amazon Web Services) #Computer Science #Maven #Data Management #Data Engineering #Code Reviews #Data Lake #S3 (Amazon Simple Storage Service) #Lambda (AWS Lambda) #Storage #DMS (Data Migration Service) #Docker #Data Governance #Jenkins #Automation #Kafka (Apache Kafka) #Data Pipeline #Informatica IDQ (Informatica Data Quality) #DynamoDB #Artifactory #AWS IAM (AWS Identity and Access Management) #Cloud #Data Quality
Role description
Senior AWS Data Engineer / DevOps Engineer
Contract Opportunity with a Major Investment Firm
Location: Newark, NJ (Hybrid – 3 days onsite per week)
Join a highly visible Enterprise Data Platform team responsible for designing and building cloud-native data solutions supporting enterprise analytics, governance, and modern data architecture initiatives. You'll work in a cutting-edge AWS environment leveraging advanced data engineering, DevOps, and data governance technologies.
This is an excellent opportunity for an experienced AWS Data Engineer who enjoys building scalable data pipelines, automating infrastructure, and working across cloud engineering, DevOps, and enterprise data platforms.
What You'll Be Working With
The environment includes several leading enterprise data management platforms, including:
• Informatica Data Catalog
• Informatica Data Marketplace
• Informatica Data Lineage
• Informatica Data Quality
• Denodo
• Ataccama
Experience with any of these platforms is considered a strong plus.
Key Responsibilities
• Design, develop, and maintain scalable AWS-based data engineering solutions.
• Build automated data ingestion pipelines from databases, APIs, file systems, and NAS shares into AWS data lakes and relational databases.
• Develop end-to-end data solutions including ingestion, storage, processing, integration, and data access.
• Design and implement modern ETL/ELT pipelines.
• Build enterprise-scale AWS Data Lake and Data Warehouse solutions.
• Develop infrastructure using Infrastructure as Code (CloudFormation).
• Build and maintain CI/CD pipelines using Jenkins and CloudBees.
• Implement DevOps best practices across AWS environments.
• Create automated deployment pipelines integrating SonarQube, security scans, and automated testing.
• Collaborate with architecture, QA, product, and engineering teams throughout the SDLC.
• Participate in Agile ceremonies including estimation, planning, code reviews, and sprint execution.
• Troubleshoot application and pipeline performance issues.
• Document technical designs, implementation decisions, issues, and lessons learned.
• Stay current with emerging AWS technologies and engineering best practices.
Required Qualifications
• Bachelor's degree in Computer Science, Information Systems, Software Engineering, or related field.
• 8+ years of Data Engineering experience.
• AWS Solutions Architect or AWS Developer Certification (required).
• Strong experience building cloud-native data platforms on AWS.
• Experience developing enterprise data ingestion pipelines.
• Strong Python, SQL, and Shell scripting experience.
• Experience with AWS Data Lake and Data Warehouse architectures.
• Experience implementing ETL/ELT solutions.
• Strong DevOps experience with CI/CD automation.
Hands-on experience with AWS services including:
• CloudFormation
• S3
• Athena
• Glue
• Glue DataBrew
• EMR / Spark
• RDS
• Aurora
• Redshift
• DynamoDB
• Lambda
• Step Functions
• IAM
• KMS
• Secrets Manager
• EventBridge
• EC2
• SQS
• SNS
• Lake Formation
• CloudWatch
• CloudTrail
• DataSync
• DMS
Preferred Experience
• Amazon Kinesis
• AWS Managed Airflow
• AWS Managed Kafka (MSK)
• Redshift RBAC
• AWS IAM security models
• Jenkins
• CloudBees
• Bitbucket
• Docker
• Maven
• Gradle
• MS Build
• SonarQube
• Artifactory
• Jira
• Confluence
• Groovy scripting
• API deployment automation
Senior AWS Data Engineer / DevOps Engineer
Contract Opportunity with a Major Investment Firm
Location: Newark, NJ (Hybrid – 3 days onsite per week)
Join a highly visible Enterprise Data Platform team responsible for designing and building cloud-native data solutions supporting enterprise analytics, governance, and modern data architecture initiatives. You'll work in a cutting-edge AWS environment leveraging advanced data engineering, DevOps, and data governance technologies.
This is an excellent opportunity for an experienced AWS Data Engineer who enjoys building scalable data pipelines, automating infrastructure, and working across cloud engineering, DevOps, and enterprise data platforms.
What You'll Be Working With
The environment includes several leading enterprise data management platforms, including:
• Informatica Data Catalog
• Informatica Data Marketplace
• Informatica Data Lineage
• Informatica Data Quality
• Denodo
• Ataccama
Experience with any of these platforms is considered a strong plus.
Key Responsibilities
• Design, develop, and maintain scalable AWS-based data engineering solutions.
• Build automated data ingestion pipelines from databases, APIs, file systems, and NAS shares into AWS data lakes and relational databases.
• Develop end-to-end data solutions including ingestion, storage, processing, integration, and data access.
• Design and implement modern ETL/ELT pipelines.
• Build enterprise-scale AWS Data Lake and Data Warehouse solutions.
• Develop infrastructure using Infrastructure as Code (CloudFormation).
• Build and maintain CI/CD pipelines using Jenkins and CloudBees.
• Implement DevOps best practices across AWS environments.
• Create automated deployment pipelines integrating SonarQube, security scans, and automated testing.
• Collaborate with architecture, QA, product, and engineering teams throughout the SDLC.
• Participate in Agile ceremonies including estimation, planning, code reviews, and sprint execution.
• Troubleshoot application and pipeline performance issues.
• Document technical designs, implementation decisions, issues, and lessons learned.
• Stay current with emerging AWS technologies and engineering best practices.
Required Qualifications
• Bachelor's degree in Computer Science, Information Systems, Software Engineering, or related field.
• 8+ years of Data Engineering experience.
• AWS Solutions Architect or AWS Developer Certification (required).
• Strong experience building cloud-native data platforms on AWS.
• Experience developing enterprise data ingestion pipelines.
• Strong Python, SQL, and Shell scripting experience.
• Experience with AWS Data Lake and Data Warehouse architectures.
• Experience implementing ETL/ELT solutions.
• Strong DevOps experience with CI/CD automation.
Hands-on experience with AWS services including:
• CloudFormation
• S3
• Athena
• Glue
• Glue DataBrew
• EMR / Spark
• RDS
• Aurora
• Redshift
• DynamoDB
• Lambda
• Step Functions
• IAM
• KMS
• Secrets Manager
• EventBridge
• EC2
• SQS
• SNS
• Lake Formation
• CloudWatch
• CloudTrail
• DataSync
• DMS
Preferred Experience
• Amazon Kinesis
• AWS Managed Airflow
• AWS Managed Kafka (MSK)
• Redshift RBAC
• AWS IAM security models
• Jenkins
• CloudBees
• Bitbucket
• Docker
• Maven
• Gradle
• MS Build
• SonarQube
• Artifactory
• Jira
• Confluence
• Groovy scripting
• API deployment automation






