AWS Enterprise Data warehouse Architect(W2, EST Candidates only))

Overview

Remote
75
Contract - W2
Contract - 12 Month(s)
No Travel Required
Unable to Provide Sponsorship

Skills

AWS data services
ETL/ELT
S3
Redshift
DynamoDB
IAM
CloudWatc

Job Details

AWS Enterprise Datawarehouse Architect-Exclusive

Remote

Web Cam Interview Only

$75 per hour W2

 

An AWS Data Warehouse Architect designs, builds, and manages scalable, secure, high-performance data platforms on AWS, focusing on data lakes, warehouses (like Redshift), ETL/ELT pipelines (Glue, EMR, PySpark), data modeling, governance, and security, while collaborating with stakeholders to translate business needs into robust data solutions using AWS services for analytics, ML, and reporting.

 

Key Responsibilities:

·       Architecture & Design: Define overall data architecture, data models, and blueprints for data lakes, warehouses, and data marts on AWS.

·       Data Ingestion & Processing: Design and implement robust ETL/ELT pipelines using services like AWS Glue, EMR, Lambda, Kinesis.

·       Data Modeling: Develop conceptual, logical, and physical data models for various workloads, ensuring performance and scalability.

·       Cloud Services Expertise: Leverage AWS services like S3, Redshift, DynamoDB, IAM, CloudWatch, and SageMaker.

·       Data Governance & Security: Implement data security, access controls (IAM), encryption, and data cataloging strategies.

·       Performance & Optimization: Tune and optimize data warehouses, data lakes, and pipelines for cost and performance.

·       Collaboration: Work with data engineers, analysts, and business stakeholders to understand requirements and deliver solutions.

·       Leadership: Mentor teams, provide technical guidance, and stay updated on emerging technologies.

 

Essential Skills & Qualifications:

·       Proven experience as a Data Architect or similar role.

·       Deep expertise in AWS data services (Glue, Redshift, S3, EMR, Lake Formation).

·       Strong SQL skills and experience with data modeling.

·       Proficiency in programming languages (Python, PySpark).

·       Experience with data orchestration tools and DevOps practices.

·       Understanding of data governance and compliance.

·       Excellent communication and leadership abilities

 

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

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