AWS Data Engineer

MACHINE LEARNING TECHNOLOGIES LLC

New Jersey

On-site

USD 140,000 - 170,000

Full time

7 hours ago

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Job summary

Machine Learning Technologies LLC is seeking an experienced AWS Data Engineer in New Jersey to design and maintain scalable data pipelines in the AWS cloud. You will collaborate with data scientists, analysts, and stakeholders to deliver robust data solutions.

The role requires 8+ years of experience with data lakes/warehouses on AWS, strong Python, SQL, and shell scripting skills, and familiarity with serverless architectures and CI/CD practices.

Qualifications

Bachelor’s degree in Computer Science, Software Engineering, MIS, or equivalent combination of education and experience.
8+ 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.

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.

Skills

AWS

Python

PySpark

Shell scripting

SQL

Education

Bachelor’s degree

Tools

CloudFormation

Athena

Glue

EMR/Spark

RDS

Redshift

DynamoDB

Lambda

Step Functions

IAM

KMS

Secrets Manager

Job description

Client:

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About
Adaptive AI
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Consulting
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Contact Us

Job Description

Job ID: J53365

Job Title: AWS Data Engineer

Location: New jersey, NJ

Duration: 24 Months + Extension

Domain Exposure: Manufacturing

Work Authorization: US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, L2-EAD, GC-EAD

Client: To Be Discussed Later

Employment Type: W-2, 1099, C2C

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Minimum of 8 years of experience. Strong AWS, Python, and PySpark experience.

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.
8+ 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.

Equal Opportunity Employer

We are an equal opportunity employer.

All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs.

We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.