Apptad - Solution Architect - Data Engineering (10-15 yrs)

Solution Architects (DWH / MASTER DATA MGT / ETL) - Pharma/Life Science/ Healthcare domain is mandatory

Job Description :

Must Have :

- Strong Verbal & Written Communications Skills

- Ability to interact with client during all US operating hours

Core Skills :

Enterprise Data Architecture & Solution Design :

- Expertise in designing scalable, multi-tenant data architectures for Life Sciences, Pharma, and Healthcare Data Platforms.

- Strong experience in delivering Data Warehouse (DWH) and Patient Data Aggregation implementations for Pharma clients.

- Deep understanding of Data Warehousing concepts, including Fact/Dimension modeling, Type 1/Type 2 SCD, and Data Mart design.

- Experience designing Conformed Dimensions via MDM Integration and aligning data models with Pharma industry standards.

- Experience with metadata-driven and modular data processing architectures for large-scale patient data aggregation.

Data Integration & ETL/ELT Frameworks :

- Strong experience with ETL/ELT tools like DBT, Python, SSIS, Informatica, or PowerCenter for high-volume Pharma data integration.

- Expertise in data orchestration frameworks, scheduling, and workflow automation.

- Experience with batch and real-time data processing pipelines.

- Extensive experience with Snowflake, including performance tuning, cost optimization, and multi-tenant architectures.

- Experience delivering Azure or AWS-based data solutions (Data Lake, Event Hubs, Lambda, Glue, etc.) in Life Sciences/Pharma settings.

- Familiarity with Data Security, Access Control, and Compliance (HIPAA, GDPR, GxP, and 21 CFR Part 11) for Pharma clients.

MDM & Data Governance :

- Expertise in Master Data Management (MDM) integration for conformed dimensions and golden records, ensuring data harmonization across Pharma and Clinical Data sources.

- Experience implementing data governance strategies for patient data aggregation, clinical trials, and commercial pharma datasets.

- Knowledge of data lineage tracking, metadata management, and data quality frameworks to support regulatory compliance in Pharma.

Roles and Responsibilities :

- Lead architecture design and implementation of Data Warehousing (DWH) and Patient Data Aggregation solutions for Pharma clients.

- Define data integration strategies across ETL/ELT, MDM, and BI layers, ensuring seamless interoperability between Pharma, Payer, and Provider data sources.

- Design and optimize multi-tenant, scalable data platforms on Snowflake to support Life Sciences data workloads.

- Establish best practices for data modeling, governance, and security in Pharma & Healthcare environments.

- Provide technical leadership to Data Engineers, DBT Developers, and Data Scientists for building scalable data pipelines.

- Define data orchestration and transformation frameworks to ensure accurate, real-time, and compliant patient data aggregation.

- Work closely with client IT and business stakeholders to align architecture decisions with business needs and regulatory requirements.

- Implement data security, privacy, and compliance standards specific to Pharma, including HIPAA, GDPR, and GxP.

- Define MDM integration strategies for harmonizing Pharma patient data and establishing golden records for commercial, clinical, and real-world evidence (RWE) datasets.

- Lead data quality initiatives, ensuring accurate, consistent, and validated patient data across multiple pharma business units.

- Collaborate with regulatory and compliance teams to ensure data platforms meet FDA, EMA, and other regulatory body requirements.

- Act as the primary technical point of contact for Pharma clients, ensuring successful project delivery.

- Collaborate with business stakeholders, data analysts, and BI teams to ensure the architecture supports analytics, reporting, and real-world evidence generation.

- Lead technical discussions, POCs, and architectural reviews for Pharma data solutions.

- Document technical architecture, best practices, and operational guidelines for DWH and Patient Data Aggregation implementations.

Preferred Qualifications :

- Bachelor's or Master's degree in Computer Science, Data Engineering, or related field.

- 10+ years of experience in Data Architecture, Solution Design, or Data Engineering.

- 5+ years working with Snowflake, DBT, and modern cloud-based data platforms in Pharma/Life Sciences.

- Proven experience delivering Data Warehousing (DWH) and Patient Data Aggregation solutions for Pharma clients.

- Experience with Pharma data domains, including EMR, Claims, EHR, Clinical Trials, and Real-World Data (RWD).

- Certifications in Snowflake, DBT, or Cloud Platforms (Azure, AWS) are a plus.

- Experience with AI/ML-driven patient data solutions is a plus.