Data Engineer - AWS

JSR Tech Consulting

Newark (NJ)

On-site

USD 171,924,480 - 200,578,560

Full time

14 days+

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Job summary

JSR Tech Consulting is seeking an AWS Data Engineer to design, build, and maintain scalable data pipelines and architectures in the AWS cloud. You will work with data scientists and analysts to deliver robust data solutions in a hybrid Newark, NJ environment.

The role requires 5+ years of experience with data lakes/warehouses on AWS, strong Python/SQL skills, and hands-on experience with services like Glue, Redshift, S3, Lambda, EMR/Spark, Kinesis, and SQS.

Qualifications

  • Bachelor's degree or equivalent combination of education and experience.
  • 5+ years of experience implementing and supporting data lakes, data warehouses, and data applications on AWS for large enterprises.
  • Strong programming experience with Python, Shell scripting, and SQL.
  • Experience with AWS services and serverless architectures.
  • Experience in ETL/ELT, data modeling, and cloud data warehousing.

Responsibilities

  • Design, build, and maintain data pipelines and applications on AWS.
  • Create data ingestion pipelines from on-prem to AWS and within AWS.
  • Develop and manage ETL/ELT processes across multiple sources.
  • Architect end-to-end data solutions focusing on data lakes and data warehouses.
  • Participate in architecture discussions for high-scale data projects.
  • Perform hands-on development, unit testing, and code reviews.
  • Implement serverless apps using AWS Lambda, API Gateway, Step Functions.
  • Migrate data to AWS-based data lakes (S3), RDS/Aurora, and Redshift.
  • Implement streaming with Kinesis, SQS, and Kafka (preferred).
  • Design CI/CD strategies for enterprise data platforms.
  • Collaborate with product, operations, and QA teams throughout SDLC.
  • Stay updated with new tools and perform POCs for real-world use cases.
  • Identify and resolve performance issues, optimize cost, reliability, and scalability.

Skills

Python
SQL
Shell scripting
Data lakes/warehouses on AWS
ETL/ELT
Data modeling
Big data concepts
Serverless development
CI/CD
AWS services
CloudFormation
Kinesis
S3
Redshift
RDS/Aurora
Glue/EMR/Spark
DynamoDB
IAM/KMS/Secrets Manager

Education

Bachelor's degree in Computer Science / Software Engineering / MIS or equivalent

Tools

AWS services: CloudFormation, S3, Athena, Glue, EMR/Spark, RDS, Redshift, DynamoDB, Lambda, Step Functions, IAM, KMS, Secrets Manager

Job description

Data Engineers (AWS)

Contract positions for a major investment firm. Hybrid work environment in Newark, NJ.

Job Summary

We are seeking a talented AWS Data Engineer to join our dynamic Data Engineering team. The ideal candidate will be responsible for designing, developing, and maintaining scalable data pipelines and architectures in the AWS cloud environment. This role will collaborate closely with data scientists, analysts, and other business stakeholders to deliver robust data solutions.

Key Responsibilities
  • Design, build, and maintain efficient, reusable, and reliable architecture and code for data pipelines and data applications on AWS.
  • Build robust data ingestion pipelines (from on‑prem to AWS and within AWS) using AWS services such as Glue, Redshift, S3, Lambda, EMR/Spark, Kinesis, and SQS.
  • Develop and manage ETL/ELT processes to collect, process, and store data from multiple sources, ensuring data quality, integrity, and security.
  • Architect and implement end-to-end data solutions (ingestion, storage, integration, processing, access) on AWS, with a focus on data lakes and data warehouses.
  • Participate in the architecture and system design discussions for high-scale data engineering projects.
  • Independently perform hands‑on development, unit testing, and participate in code reviews to ensure adherence to best practices.
  • Implement serverless applications using AWS Lambda, API Gateway, Step Functions, and other AWS technologies.
  • Migrate data from traditional relational databases, file systems, and APIs to AWS-based data lakes (S3), RDS, Aurora, and Redshift.
  • Implement high‑velocity streaming solutions using Amazon Kinesis, SQS, and Kafka (preferred).
  • Architect and implement CI/CD strategies for enterprise data platforms.
  • Collaborate with product, operations, QA, and cross‑functional teams throughout the software development cycle.
  • Stay abreast of new technology developments, implement POCs for new tools/technologies, and onboard them for real-world use cases.
  • Identify and resolve performance issues and continuously optimize for cost, reliability, and scalability.
Required Qualifications
  • Bachelor's degree in Computer Science, Software Engineering, MIS, or equivalent combination of education and experience.
  • 5+ years of experience implementing and supporting data lakes, data warehouses, and data applications on AWS for large enterprises.
  • Strong programming experience with Python, Shell scripting, and SQL.
  • Solid experience with AWS services: CloudFormation, S3, Athena, Glue, EMR/Spark, RDS, Redshift, DynamoDB, Lambda, Step Functions, IAM, KMS, Secrets Manager.
  • Experience in serverless application development and data pipeline orchestration.
  • Experience in system analysis, design, development, and implementation of data ingestion pipelines in AWS.
  • Knowledge of ETL/ELT, data modeling, and big data technologies.
  • Familiarity with data warehousing concepts and cloud-based architecture.
  • Strong problem‑solving skills and attention to detail.
  • Excellent communication and teamwork abilities.
Preferred Qualifications
  • Experience with additional AWS services: API Gateway, ElasticSearch, SQS.
  • Experience with infrastructure‑as‑code tools (e.g., Terraform, CloudFormation).
  • Experience with DevOps practices and CI/CD pipelines.
  • Experience implementing end‑to‑end streaming solutions (Amazon Kinesis, SQS, Kafka).
  • AWS Solutions Architect or AWS Developer Certification preferred.
  • Understanding of Lakehouse/data cloud architecture.
  • Knowledge of data governance and compliance standards.

Payrate 60 - 70 per hour, depending on experience.

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