Description

You will lead the design and implementation of scalable data architectures and self-service platform capabilities.

Responsibilities

• Drive adoption of modern data stack technologies, specifically data lakehouse architecture.
• Partner with product managers, data scientists, and analysts to translate business requirements into technical solutions.
• Mentor data engineers and software engineers while providing architectural oversight during design and deployment.
• Define standards for access control, quality, cataloging, and observability across domains.
• Collaborate with security, infrastructure, and enterprise architecture teams to ensure compliance with privacy and GxP requirements.
• Evaluate emerging tools to improve scalability, performance, and cost-efficiency.
• Own architecture documentation and promote the reuse of patterns across the Data Platform.

Required Skills

• 12+ years of experience in software engineering with a focus on scalable data architectures.
• Proven expertise in architecting end-to-end data solutions on AWS.
• Deep understanding of data lakehouse architecture.
• Hands-on experience with AWS Glue, Amazon Redshift, Spark, and Apache Iceberg.
• Proficiency in Python, SQL, and dbt.
• Experience with CI/CD, infrastructure as code, and modern DevOps practices.
• Background in architecting and leading self-service data platform capabilities.
• Strong leadership skills with experience mentoring engineers and influencing stakeholders.

Preferred Skills

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

Key Skills

Education

Any Gradute