Principal Data Architect

Curium Pharma; St. Louis (MO); Hybrid; USD 150,000 - 210,000; Full time

Benefits offered by this job

Hybrid work arrangement

Job summary

Curium Pharma seeks a Principal Data Architect to shape the enterprise data architecture for BI, analytics, AI, and digital transformation. You will establish data standards, models, integration patterns, and governance to enable trusted, scalable data across the organization.

The role combines hands-on architectural leadership with collaboration across business stakeholders, data engineers, analytics teams, and technology leaders to ensure data assets align with strategic objectives.

Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Data Science, Engineering, or a related technical field, or equivalent professional experience.
• 8+ years of professional software engineering experience, including 4+ years in data management, data engineering, data warehousing, or analytics, and 2+ years of lead-level cloud data engineering.
• Demonstrated experience designing and implementing enterprise-scale data solutions that support business intelligence, analytics, operational reporting, and advanced analytics.
• Strong experience developing conceptual, logical, and physical data models, including dimensional (star and snowflake) schemas and modern data warehouse, data lake, and lakehouse architectures, using established data modeling principles and best practices.
• Strong understanding of data integration and engineering principles, including ETL/ELT processes, data pipelines, APIs, batch processing, and real-time integration patterns.
• Proficiency in SQL with a strong understanding of database design, data transformation, performance optimization, and data management principles.
• Experience with data governance practices, including data ownership, stewardship, metadata management, data lineage, data quality, master and reference data, and data cataloging.
• Experience designing solutions on modern cloud-based data platforms and analytics/distributed-data environments, such as Microsoft Fabric, Azure, Snowflake, Databricks, or comparable technologies.
• Strong understanding of data security, privacy, access management, and regulatory compliance requirements and the ability to incorporate these principles into enterprise data architecture.
• Strong communication and stakeholder management skills, able to translate complex technical concepts into clear business language, establish architecture standards, influence technical decisions, and provide technical leadership across business and technology teams without direct authority.
• Strong analytical and problem-solving skills with the ability to evaluate business requirements and translate them into scalable, secure, and maintainable data architecture solutions.

Responsibilities

• Enterprise Architecture & Data Design: Develop and maintain enterprise data strategies, roadmaps, standards, reference architectures, and documentation.
• Data Integration: Define scalable standards and patterns for ETL, ELT, APIs, batch, real-time integration, automated onboarding, and ingestion management.
• Data Governance & Quality: Establish governance and quality standards for metadata, lineage, ownership, stewardship, access, and consistent business definitions.
• Cloud & Modern Data Platforms: Design secure and resilient cloud data warehouses, lakes, and lakehouses that meet scalability, availability, performance, and cost requirements.
• Analytics & AI Enablement: Enable governed reporting, self-service analytics, AI, and reusable data products through trusted data and well-defined semantic models.
• Security & Compliance: Embed security, privacy, role-based access, and regulatory requirements into architecture designs and data protection standards.
• Architecture Leadership & Collaboration: Provide technical leadership, translate business needs into scalable solutions, and review designs for alignment with standards.

Skills

Enterprise architecture

Data modeling

ETL/ELT

SQL

Data governance

Cloud platforms

Data security & compliance

Stakeholder communication

Leadership

Education

Bachelor’s degree in CS/IS/Data Science/Engineering

Master’s degree

Data management/certification awareness

Tools

Microsoft Fabric

Azure

Snowflake

Databricks

Job description

The Principal Data Architect is responsible for designing, developing, and governing the organization's enterprise data architecture to support business intelligence, analytics, artificial intelligence, operational reporting, and digital transformation initiatives. This role establishes data standards, models, integration patterns, and governance frameworks that enable trusted, scalable, and secure data across the enterprise. The Data Architect works closely with business stakeholders, data engineers, analytics teams, application owners, and technology leaders to ensure data assets are aligned with organizational strategy and business objectives.

Work Schedule: M - F 8am - 5pm. This is a hybrid position: 4 days onsite, 1 day remote.

Job description:

Summary of Position

The Principal Data Architect is responsible for designing, developing, and governing the organization's enterprise data architecture to support business intelligence, analytics, artificial intelligence, operational reporting, and digital transformation initiatives. This role establishes data standards, models, integration patterns, and governance frameworks that enable trusted, scalable, and secure data across the enterprise. The Data Architect works closely with business stakeholders, data engineers, analytics teams, application owners, and technology leaders to ensure data assets are aligned with organizational strategy and business objectives.

Work Schedule: M - F 8am - 5pm. This is a hybrid position: 4 days onsite, 1 day remote.

Essential Functions

• Enterprise Architecture & Data Design:
  • Develop and maintain enterprise data strategies, roadmaps, standards, reference architectures, and documentation.
  • Design scalable data platforms and conceptual, logical, physical, and dimensional models for reporting, analytics, AI, and operational use.
  • Define enterprise principles for master, reference, transactional, and cross-domain data.
• Data Integration:
  • Define scalable standards and patterns for ETL, ELT, APIs, batch, real-time integration, automated onboarding, and ingestion management.
  • Design integration across applications, platforms, and data sources, partnering with Data Engineers to implement reliable solutions.
• Data Governance & Quality:
  • Establish governance and quality standards for metadata, lineage, ownership, stewardship, access, and consistent business definitions.
  • Enable trusted data products through metadata-driven auditing, monitoring, and collaboration with Data Governance teams.
• Cloud & Modern Data Platforms:
  • Design secure and resilient cloud data warehouses, lakes, and lakehouses that meet scalability, availability, performance, and cost requirements.
  • Evaluate emerging technologies, third-party solutions, and AI tooling; recommend improvements and establish usage and cost-attribution practices.
• Analytics & AI Enablement:
  • Enable governed reporting, self-service analytics, AI, and reusable data products through trusted data and well-defined semantic models.
  • Partner with analytics and AI teams to define architecture requirements and secure adoption standards.
• Security & Compliance:
  • Embed security, privacy, role-based access, and regulatory requirements into architecture designs and data protection standards.
  • Partner with Security and Compliance teams to ensure alignment with organizational and regulatory expectations.
  • Must maintain operational compliance with US and international regulatory agencies and guidelines (i.e. FDA, DEA, EU, HC, TGA, PIC/S, ISO, USP, NRC, cGMP, etc.).
• Architecture Leadership & Collaboration:
  • Provide technical leadership, translate business needs into scalable solutions, and review designs for alignment with standards.
  • Collaborate across business, technology, and governance teams while maintaining diagrams, standards, and architecture documentation.
  • Guide and mentor Data Engineers and delivery teams through architecture best practices and code reviews.

Requirements

• Must have Experience / Skills:
  • Bachelor’s degree in Computer Science, Information Systems, Data Science, Engineering, or a related technical field, or equivalent professional experience
  • 8+ years of professional software engineering experience, including 4+ years in data management, data engineering, data warehousing, or analytics, and 2+ years of lead-level cloud data engineering
  • Demonstrated experience designing and implementing enterprise-scale data solutions that support business intelligence, analytics, operational reporting, and advanced analytics.
  • Strong experience developing conceptual, logical, and physical data models, including dimensional (star and snowflake) schemas and modern data warehouse, data lake, and lakehouse architectures, using established data modeling principles and best practices.
  • Strong understanding of data integration and engineering principles, including ETL/ELT processes, data pipelines, APIs, batch processing, and real-time integration patterns.
  • Proficiency in SQL with a strong understanding of database design, data transformation, performance optimization, and data management principles.
  • Experience with data governance practices, including data ownership, stewardship, metadata management, data lineage, data quality, master and reference data, and data cataloging.
  • Experience designing solutions on modern cloud-based data platforms and analytics/distributed-data environments, such as Microsoft Fabric, Azure, Snowflake,
  • Databricks, or comparable technologies (preferred).
  • Strong understanding of data security, privacy, access management, and regulatory compliance requirements and the ability to incorporate these principles into enterprise data architecture.
  • Strong communication and stakeholder management skills, able to translate complex technical concepts into clear business language, establish architecture standards, influence technical decisions, and provide technical leadership across business and technology teams without direct authority.
  • Strong analytical and problem-solving skills with the ability to evaluate business requirements and translate them into scalable, secure, and maintainable data architecture solutions
• Nice to have Experience / Skills:
  • Master’s degree or MBA.
  • Knowledge of Agile development and the software development lifecycle.
  • Relevant certifications in data management, analytics, cloud platforms, architecture, or project management.
  • Experience with pharmaceutical regulations and guidance, including 21 CFR Part 11/210/211, EU Annex 11, MHRA, GAMP 5, cGMP, electronic records, signatures, and data integrity.
  • Additional language proficiency.