Senior AWS data engineer Job East Orange area,New Jersey USA,Software Development

Senior AWS Data Engineer

Hybrid position from Newark, NJ office.

Job Summary

Seeking a senior AWS data engineer who can drive efficient data acquisition, curation, and delivery using services such as S3 bucket, Athena, Glue, and Cloud Formation. Collaborate with cross‑functional teams in a hybrid work model to enable reliable day time operations.

Experience

7 to 11 years of experience.

Required Skills

AWS Glue
AWS
AWS Cloud Formation
AWS Athena
AWS S3 bucket

Responsibilities

Designing, building and maintaining efficient, reusable, and reliable architecture and code.
Build reliable and robust data ingestion pipelines within AWS, on‑prem to AWS, etc.
Ensure the best possible performance and quality of high‑scale data engineering projects.
Participate in the architecture and system design discussions.
Independently perform hands‑on development and unit testing of the applications.
Collaborate with the development team and build individual components into complex enterprise web systems.
Work in a team environment with product, production operation, QE and cross‑functional teams to deliver a project throughout the whole software development cycle.
Responsible to identify and resolve any performance issues.
Keep up to date with new technology development and implementation.
Participate in code review to make sure standards and best practices are met.
Experience implementing, supporting data lakes, data warehouses and data applications on AWS for large enterprises.
Programming experience with Python, shell scripting and SQL.
Solid experience of AWS services such as Cloud Formation, S3, Athena, Glue, EMR/Spark, RDS, Redshift, DynamoDB, Lambda, Step Functions, IAM, KMS, SM etc.
Solid experience implementing solutions on AWS based data lakes.
Should have good experience with AWS services like API Gateway, Lambda, Step Functions, SQS, DynamoDB, S3, Elasticsearch.
Serverless application development using AWS Lambda.
Experience in AWS data lake/data warehouse/business analytics.
Experience in system analysis, design, development, and implementation of data ingestion pipeline in AWS.
Knowledge of ETL or ELT end‑to‑end data solutions (ingest, storage, integration, processing, access) on AWS.
Architect and implement CI or CD strategy for EDP.
Implement high‑velocity streaming solutions using Amazon Kinesis, SQS, and Kafka (preferred).
Migrate data from traditional relational database systems, file systems, NAS shares to AWS relational databases such as Amazon RDS, Aurora, and Redshift.
Migrate data from APIs to AWS data lake (S3) and relational databases such as Amazon RDS, Aurora, and Redshift.
Implement POCs on any new technology or tools to be implemented on EDP and onboard for real use‑case.
AWS Solutions Architect or AWS Developer Certification preferred.
Good understanding of lakehouse/data cloud architecture.

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