Senior Data Architect

The Senior Data Architect will lead the design and implementation of scalable, high-performance data architectures across both on-premise and cloud environments. This role involves advanced data modeling, SQL development, and ETL design, with a strong focus on data quality, integrity, and strategy. The architect will collaborate closely with cross-functional teams to align technical solutions with business needs, perform in-depth data analysis, and drive the development of robust data models that support long-term organizational goals.

• Data Architecture & Strategy
• Advanced Data Modeling (Star, Snowflake)
• SQL Development (Partitioning, Stored Procedures, Recursive Queries)
• Data Profiling & Root Cause Analysis
• ETL Design & Implementation
• Cloud & On-Premise Data Platforms (Oracle, Databricks)
• Data Quality & Governance
• Stakeholder Engagement
• Change Data Capture & Audit Strategy
• Cross-Functional Collaboration
  

• Analyze existing data sources to understand data flow, relationships, and usage.
• Design and implement scalable data models following best practices in normalization, denormalization, and dimensional modeling.
• Develop and optimize complex SQL queries, including recursive SQLs and macros, to extract, transform, and analyze data.
• Architect end-to-end data strategies aligned with future-state objectives, focusing on performance, scalability, and flexibility.
• Reverse engineer data models through data profiling, identifying key attributes and relationships.
• Collaborate with business and technical stakeholders to map data patterns to underlying processes and use cases.
• Conduct root cause analysis (RCA) to troubleshoot data inconsistencies and propose effective resolutions.
• Perform frequency distribution and statistical analyses to detect data trends and quality issues.
• Design and implement change data capture (CDC), audit logging, and reference data strategies.
• Define and create mapping tables and helper tables to support flexible and configurable ETL processes.
• Own and ensure data integrity, accuracy, and completeness across platforms.
  

• Demonstrates intellectual curiosity and passion for uncovering insights in complex datasets.
• Skilled communicator capable of translating technical concepts into actionable insights for diverse stakeholders.
• Engages effectively with clinicians, researchers, data scientists, and IT teams to gather requirements and align objectives.
• Leads deep-dive data analysis initiatives to support data-driven decision-making.
• Collaborates across departments to deliver robust, business-aligned data models and solutions.
  

• Familiarity with data visualization tools (e.g., Tableau, Power BI) is an advantage.
• Experience in the Life Sciences or Pharmaceutical industry is highly desirable.