Veracity
Cloud Data Architect
Ridgefield, Connecticut
Work Type:
Full-Time | Hybrid The
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.
Full-Time | Hybrid The
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.