Senior Enterprise Architect

This is a fully remote position, open to applicants in Canada.

📋 Description

• Take ownership of the enterprise data architecture blueprint, principles, and reference patterns pertaining to ingestion, storage, transformation, and serving.

• Develop reference architectures for batch processing, Change Data Capture (CDC), near-real-time streaming, semantic layers, and federated queries.

• Establish data modeling guidelines across operational, analytical, and clinical-standard data domains.

• Assess and govern technology choices in alignment with the overarching technology strategy of the company.

• Collaborate with product and engineering teams on data contracts and schema definitions.

• Design a storage strategy encompassing lakehouse, warehouse, operational, and archival tiers.

• Define data delivery mechanisms for Business Intelligence (BI), embedded analytics, machine learning/artificial intelligence (ML/AI) workloads, regulatory submissions, and sponsor data exchange.

• Co-manage data security controls in conjunction with the Information Security team, including encryption, tokenization, access management, and auditing processes.

• Lay the groundwork for governance, Master Data Management (MDM), data quality assurance, metadata management, and cataloging.

• Establish standards for CI/CD, observability, data testing, incident management, and orchestration.

• Act as the data authority on the Architecture Review Board.

• Evaluate data vendors and SaaS platforms regarding architectural compatibility, data residency, GxP compliance, and total cost of ownership.

• Create architecture decision records, reference implementations, and training materials.

• Lead a data maturity initiative and communicate progress to R&D leadership.

• Collaborate closely with the Senior Director of Data & Analytics.

• Report directly to the Chief Enterprise Architect.

⛳️ Requirements

• A minimum of 5 years in data-intensive roles, including over 5 years in senior data architecture or principal/staff-level data engineering.

• Hands-on experience with the complete data engineering lifecycle, from data generation to serving, in a production environment.

• Proven track record of significantly enhancing an organization’s data maturity.

• Experience collaborating within or alongside an Enterprise Architecture function or Architecture Review Board.

• Proficiency in SQL and Python (or another data engineering language), with the ability to review production pipeline code.

• Familiarity with batch and streaming ingestion, including CDC and event streaming technologies (e.g., Kafka or similar).

• Practical knowledge of orchestration tools (e.g., Airflow or similar), data modeling, and transformation frameworks.

• Working knowledge of relational and document databases, including PostgreSQL, Oracle, SQL Server, and MongoDB.

• Awareness of MDM concepts and experience with at least one MDM platform.

• Experience in designing solutions on AWS or a comparable cloud provider, with a focus on cost efficiency, security, and operability.

• Nice to have: experience in clinical research, pharmaceuticals, biotechnology, medical technology, or other GCP-regulated environments.

• Nice to have: knowledge of CDISC standards (ODM, SDTM, ADaM) and clinical data domains.

• Nice to have: exposure to AI/ML platform architecture, including feature stores, vector stores, RAG pipelines, and MLOps.

🏝️ Benefits

• Competitive salary and performance-based incentives.

• Comprehensive health and wellness benefits.

• Opportunities for professional development and continuous learning.

• Flexible work arrangements to promote work-life balance.

• Collaborative and innovative work environment.