What are the responsibilities and job description for the Sr Data Architect - Patient Services (Life Sciences) position at Tiger Analytics Inc.?
Tiger Analytics is pioneering what AI and analytics can do to solve some of the toughest problems faced by organizations globally. We develop bespoke solutions powered by data and technology for several Fortune 100 companies. We have offices in multiple cities across the US, UK, India, and Singapore, and a substantial remote global workforce.
We are seeking a Data Architect – Patient Services to join our Life Sciences practice. In this role, you will be responsible for ensuring the integrity and reliability of Patient Services (PS) data and be the primary bridge between external Patient Services Hub vendors and internal enterprise systems. This is a high-impact role combining technical data modeling with operational stewardship, requiring you to drive data quality, investigate complex lineage issues, and ensure that patient data is "analytics-ready" for strategic decision-making.
Responsibilities:
- Architecture & Modeling: Lead source-to-target mapping from external Hub vendors to internal systems (EDB). Define logical/conceptual data models and act as the primary SME for Patient Services data structures.
- Data Stewardship: Partner with MDM teams to ensure accurate HCO mastering and hierarchy aggregation. Identify data gaps and design solutions to roll up Patient Access data across therapeutic areas.
- Quality & Integrity: Proactively resolve data issues and define validation rules. Collaborate with DD&T to implement data quality checks within the pipeline ecosystem.
- Vendor Accountability: Direct engagement with PS Hub vendors and aggregators to investigate root causes, enforce Data SLAs, and validate data fixes before and after transmission.
- Analytics Enablement: Partner with Analytics & Insights (A&I) to build "Analytics Ready Data" (ARD) layers, ensuring data is reliable, actionable, and compliant with audit standards.
- 15 yrs of experience in data architecture, data management, or data engineering roles.
- Strong experience with healthcare, patient services, or life sciences data (mandatory).
- Demonstrated expertise in data quality management, validation, and issue resolution.
- Experience working with external vendors and complex data pipelines.
- Strong SQL skills and experience querying enterprise data platforms.
- Proven ability to translate business needs into data requirements and quality rules.
- Experience supporting Patient Services / Hub data in a pharmaceutical or biopharma environment.
- Familiarity with enterprise data warehouses (e.g., Snowflake, Oracle, Teradata) and data lakes.
- Knowledge of data governance frameworks and master/reference data concepts.
- Ability to operate in a matrixed, cross functional environment.
Key Competencies
- Data ownership mindset and attention to detail
- Strong analytical and problem-solving skills
- Clear communicator with technical and nontechnical partners
- Comfortable driving accountability across vendors and stakeholders
- Able to balance operational rigor with strategic impact
Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging, and entrepreneurial environment, with a high degree of individual responsibility.
Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.