Teams at IntegriChain

Designs and maintains scalable data pipelines, warehouse models, data marts, and dimensional structures using dbt, Python, SQL, and ELT tools. Implements slowly changing dimensions, integrates MDM systems, ensures data quality across life sciences and healthcare datasets, and collaborates with analysts, data scientists, and engineers to deliver trusted datasets for analytics and decision-making.

The Product Analyst translates business needs into requirements, user stories, workflows, and technical specifications. They support agile delivery, backlog refinement, sprint planning, QA clarification, defect triage, documentation, release support, and stakeholder collaboration. The role also applies AI and automation to improve product development and business processes while developing expertise in pharmaceutical and life sciences data and regulatory requirements.

Owns QA strategy and automation architecture across application, data, ETL/ELT, API, UI, BDD, and performance testing. Builds Python-based frameworks and data validation libraries using SQL, pandas, and PySpark; develops Playwright and JMeter test suites; analyzes failures and performance results; and ensures coverage of biopharma requirements and regulatory risks. The role partners cross-functionally, communicates quality status, mentors junior engineers, supports incident response, evaluates AI testing tools, and drives team-level quality improvements.