Senior Enterprise Architect
Key Skills for This Role
Full Job Posting
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.
About Clario
Clario is a clinical-trial endpoint technology company serving pharmaceutical, biotech, and medical-device sponsors.
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