AWS DATA ENGINEER

Overview

Hybrid
42 - 45
Contract - Independent
Contract - W2
Contract - 12 Month(s)
No Travel Required
Unable to Provide Sponsorship

Skills

AWS
S3
LAMBDA

Job Details

8+ YEARS OF TOTAL EXP designs, builds, and maintains scalable data infrastructure on AWS, focusing on creating robust data pipelines (ETL/ELT) using services like S3, Glue, Redshift, Kinesis, Lambda to ingest, process, and store large datasets, ensuring data quality, security, performance, and accessibility for analytics and ML, collaborating closely with data scientists and analysts. Key tasks involve data modeling, automation, monitoring, optimization, and implementing security/compliance measures within the AWS ecosystem. 
 
Core Responsibilities
    • : Build and manage automated pipelines (batch/streaming) using AWS Glue, Lambda, Kinesis, Step Functions, Airflow for data ingestion (ETL/ELT).
    • : Design and maintain scalable data lakes (S3) and data warehouses (Redshift).

: Connect diverse data sources (APIs, databases, files) and ensure data consistency.: Create efficient data models and manage storage on S3, RDS, DynamoDB, etc..: Tune pipelines, queries, and AWS resources for speed and cost-efficiency.: Implement data validation, access controls (IAM), encryption (KMS), and compliance.: Automate tasks, build reusable frameworks, and provide operational support (Run/DevOps). 

 

Key AWS Services Used

  • Storage: , , , .
  • Processing: , , , .
  • Orchestration: , .
  • Security: , . 

 

Collaboration & Business Alignment 

  • Work with Data Scientists, Analysts, and business stakeholders to meet data requirements.
  • Translate business needs into technical data solutions.
  • Provide clear communication to both technical and non-technical audiences. 

 

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