Senior Enterprise Architect

Job description

Clario, part of Thermo Fisher Scientific, is a global leader in clinical trial technology. We combine deep scientific expertise with the industry’s broadest endpoint collection platform to help pharmaceutical and biotechnology companies deliver life-changing therapies to patients. Our clinical data operations span a highly regulated, patient-centric landscape, from first-in-human trials to large-scale Phase IV programs. The volume, velocity, and variety of the data we generate are growing fast. To keep pace, we’re building a next-generation, enterprise-grade Data & Analytics platform that unifies clinical, operational, and commercial data under a single architectural vision. As our Senior Data Architect, you’ll sit where architecture meets data engineering. You’ll set the target-state data architecture for the enterprise and define the technology and pattern choices our engineering teams build against. You’ll be the senior technical authority for everything between our raw clinical and operational source systems and the analytical, AI, and regulatory consumers of that data. This is a hands-on senior individual contributor role reporting to the Chief Enterprise Architect. You’ll earn architectural authority through technical credibility, so expect to spend real time in code, in data, and in design documents, not just in slide decks. What You’ll Be Doing Architecture and Patterns Own the enterprise data architecture blueprint, principles, and reference patterns across ingestion, storage, transformation, and serving Define reference architectures for batch, CDC, near-real-time streaming, semantic layer design, and federated query, choosing the right pattern for each use case Set data modeling direction across operational, analytical, and clinical-standard data, and define how they map to one another Evaluate and govern technology choices in line with the company-wide technology strategy Data Lifecycle Partner with product and engineering teams so data contracts and schemas are designed for downstream use from the start Design the storage strategy across lakehouse, warehouse, operational, and archival tiers Define how data reaches BI (Power BI, Plotly), embedded analytics in our clinical applications, ML/AI workloads, regulatory submissions, and sponsor data exchange Security, Governance and DataOps Co-own data security controls with InfoSec, including encryption, tokenization, access management, and audit Set the architectural foundation for governance, MDM (Reltio), data quality, metadata, and cataloging Establish CI/CD, observability, data testing, and incident management standards for pipelines, and define orchestration architecture across Airflow and related tools Leadership and Enablement Serve as the data authority on the Architecture Review Board, reviewing major architecture changes and new data products Assess data vendors and SaaS platforms for architectural fit, data residency, GxP suitability, and total cost of ownership Produce architecture decision records, reference implementations, and training so teams can make sound architectural choices on their own Lead a data maturity program across people, process, and technology, reporting progress to R&D leadership on quality, time-to-data, cost, and risk Partner closely with the Senior Director of Data & Analytics, whose teams are your primary delivery partners What We Look For 5+ years in data-intensive roles, including 5+ years in senior data architecture or principal/staff-level data engineering Hands-on ownership of the full data engineering lifecycle, from generation through serving, in production A track record of measurably improving an organization’s data maturity Experience working within or alongside an Enterprise Architecture function or Architecture Review Board Fluency in SQL and Python (or another data engineering language), with the ability to review production pipeline code Experience with batch and streaming ingestion, including CDC and event streaming (Kafka or equivalent) Practical experience with orchestration (Airflow or equivalent), data modeling, and transformation frameworks Working knowledge of relational and document databases (PostgreSQL, Oracle, SQL Server, MongoDB) and the trade-offs between operational and analytical stores Familiarity with MDM concepts and at least one MDM platform Experience designing on AWS or a comparable cloud provider, with attention to cost, security, and operability Nice to Have Experience in clinical research, pharma, biotech, medtech, or another GCP-regulated environment Knowledge of CDISC standards (ODM, SDTM, ADaM) and clinical data domains such as eCOA, Cardiac Safety, Respiratory, and Imaging Exposure to AI/ML platform architecture (feature stores, vector stores, RAG pipelines, MLOps) The duties and responsibilities listed in this job description represent the major responsibilities of the position. Other duties and responsibilities may be assigned, as required. Clario reserves the right to amend or change this job description to meet the needs of Clario. This job description and any attachments do not constitute or represent a contract. The Department Head has the discretion to hire personnel with a combination of experience and education, which may vary from the above listed qualifications.