Cloud Data Architect Ridgefield, Connecticut Work Type: Full-Time | HybridThe Cloud Data Architect will lead the design, implementation, and management of scalable cloud-based data solutions to support the company's commercial and medical data analytics initiatives. This role plays a critical part in the development and governance of enterprise data architectures that power analytics, AI, and digital products. The ideal candidate has strong experience in AWS-based cloud data platforms, semantic data modeling, and data pipeline optimization, with specific exposure to pharmaceutical commercial data domains.
Key Responsibilities:
Design and implement efficient, scalable, and secure Cloud Data Architecture on AWS.Develop logical and physical data models and database designs to support enterprise data strategy.
Collaborate with cross-functional teams to translate business data needs into technical architecture.
Partner with Data Domain Owners to establish Data Governance and Data Sharing Terms policies.
Optimize database performance, ensuring data quality, availability, and reliability.
Lead data modernization initiatives and migrate legacy systems to cloud-based environments.
Build and maintain data pipelines for ingestion, transformation, and analytics enablement (structured and unstructured data).Develop and implement semantic data models, knowledge graphs, and AI-driven data frameworks (e.g., NLP, recommendations, predictive analytics).Stay current on cloud computing, data architecture, and analytics trends; evaluate and recommend emerging technologies.
Provide technical mentorship to developers, engineers, and analysts within the data organization.
Required Qualifications
Education:
Bachelor's degree in Computer Science, Information Technology, Engineering, or related field. In lieu of degree: 10+ years of relevant IT experience.
Experience:
7+ years in data architecture, data management, or business intelligence, with at least 5+ years of hands-on cloud (AWS) experience. Proven track record of leading large-scale cloud modernization or data migration projects. At least 5 years of pharma industry experience, preferably in commercial data domains. Experience in data governance, ETL design, and data pipeline optimization.
Technical Expertise: AWS Cloud Services (S3, Glue, Redshift, Lambda, IAM). Snowflake, Apache Parquet, DBT, SnapLogic, SQL/NoSQL. Data modeling, data lake architecture, and metadata management. Knowledge Graphs, ontologies, and AI-driven semantic data modeling.
Soft Skills: Strong analytical, problem-solving, and collaboration skills. Excellent written and verbal communication. Ability to explain and defend architectural decisions.
Preferred Qualifications
Certifications: AWS Certified Solutions Architect preferred.
Experience:
GxP processes, Innovator platform, or similar life sciences data systems.
Methodologies: Familiarity with Agile/Scrum delivery models.
Leadership: Ability to guide technical discussions and mentor junior engineers.
