AWS Senior Data Architect

Job Summary

The AWS Data Architecture Lead is responsible for architecting and delivering large-scale, enterprise-grade data solutions using Amazon Glue, Redshift, Snowflake, and Python within a DevOps-enabled environment. This role provides architectural leadership, drives technical strategy, and ensures solutions are robust, scalable, and aligned with industry best practices. The position is pivotal in bridging business requirements with advanced data engineering, fostering innovation, and maintaining technical excellence across projects.

Key Responsibilities

1. Architect And Design Enterprise Data Pipelines And Etl Workflows Using Amazon Glue, Ensuring Scalable, Secure, And Efficient Data Integration Across Multiple Sources.
2. Define And Implement Data Warehousing Solutions Leveraging Amazon Redshift And Snowflake, Optimizing For Performance, Cost, And Reliability.
3. Lead The Adoption Of Devops Practices For Data Engineering By Automating Deployment, Monitoring, And Ci/Cd Pipelines For Aws-Based Data Platforms.
4. Provide Architectural Governance By Reviewing And Validating Solution Designs, Ensuring Compliance With Organizational And Industry Standards.
5. Guide The Team In Developing Advanced Data Transformation Scripts Using Python, Enabling Complex Data Processing And Analytics Use Cases.
6. Drive Technology Innovation By Evaluating Emerging Aws Services And Data Engineering Tools, Recommending Adoption To Enhance Solution Capabilities.
7. Mentor And Upskill Team Members In Amazon Glue, Redshift, Snowflake, And Python, Fostering A Culture Of Continuous Learning And Technical Excellence.
8. Represent The Organization By Submitting Whitepapers, Participating In Industry Forums, And Contributing To Patent Filings In The Data Architecture Domain.

Skill Requirements

1. Architectural Leadership In Amazon Glue For Designing And Orchestrating Complex Etl Solutions.
2. Advanced Proficiency In Amazon Redshift And Snowflake For Data Warehousing And Analytics.
3. ExpertLevel Skills In Python For Data Engineering And Automation Tasks.
4. InDepth Experience With Devops Practices And Tools (E.G., Aws Codepipeline, Cloudformation, Terraform) For Data Platform Automation.
5. Solid Understanding Of Data Governance, Security, And Compliance Within Aws Environments.
6. Excellent Ability To Translate Business Requirements Into Scalable, CloudNative Data Architectures.

Other Requirements

1. Aws Certified Solutions Architect � Professional (Recommended)
2. Aws Certified Data Analytics � Specialty (Optional But Valuable)
3. Snowflake Snowpro Advanced Architect Certification (Optional But Valuable