Job Description

The Role Architect and lead implementation of Data platform self-service capabilities across ingestion, processing, storage, and consumption layers

• Drive adoption of modern data stack technologies and best practices (e.g., data lakehouse architecture).
• Partner with product managers, data scientists, analysts, and engineering teams to translate business needs into scalable technical solutions.
• Mentor data engineers and provide architectural oversight during design, implementation, and deployment phases.
• Define and enforce standards for access control, quality, cataloging, and observability across domains.
• Provide hands-on leadership and technical mentorship to Software engineers, data engineers and platform developers.
• Collaborate with enterprise architecture, security, and infrastructure teams to align with broader org standards and policies.
• Evaluate emerging tools and technologies in the data ecosystem and recommend solutions to improve scalability, performance, and cost-efficiency.
• Own architecture documentation and promote reuse of patterns and capabilities across Data Platform.
• Ensure platform compliance with data privacy and security requirements (e.g., GxP).

Break into Basic Qualifications and Preferred Qualifications

Basic Qualifications:

• Over 8 years of experience in software engineering, with a strong focus on designing and implementing scalable data architectures. Proven expertise in architecting end-to-end data solutions on AWS
• Background in architecting and leading self-service data platform capabilities
• Deep understanding of data lakehouse architecture
• Hands-on experience with data services such as AWS Glue, Amazon Redshift, as well as proficiency in Python, SQL, and dbt, spark and apache iceberg
• Hands-on experience with CI/CD, infrastructure as code, and modern DevOps practices
• Experience leading teams or mentoring junior engineers.
• Excellent communication and leadership skills with the ability to influence both technical and non-technical stakeholders

Preferred Qualifications:

• Experience with data governance frameworks, lineage, cataloging, and metadata management
• Familiarity with data privacy, compliance, and security best practices.
• Prior experience working in a highly collaborative environment with product, data science, and analytics teams.

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