Indegene - Associate Manager - Data Engineering

: We are a technology-led healthcare solutions provider. We are driven by our purpose to enable healthcare organizations to be future-ready. We offer accelerated, global growth opportunities for talent that's bold, industrious, and nimble. With Indegene, you gain a unique career experience that celebrates entrepreneurship and is guided by passion, innovation, collaboration, and empathy. Looking to jump-start your career? We understand how important the first few years of your career are, which create the foundation of your entire professional journey. At Indegene, we promise you a differentiated career experience. You will not only work at the exciting intersection of healthcare and technology but also will be mentored by some of the most brilliant minds in the industry. We are offering a global fast-track career where you can grow along with Indegene's high-speed growth. We are purpose-driven. We enable healthcare organizations to be future ready and our customer obsession is our driving force. We ensure that our customers achieve what they truly want. We are bold in our actions, nimble in our decision-making, and industrious in the way we work. Role : Associate Manager - Data Engineering Job Description : The Associate Manager Data Engineering will lead the design, development, and optimization of data pipelines and platforms supporting analytics, AI/ML, and reporting solutions for pharmaceutical clients. The role requires strong technical expertise, pharma domain knowledge, and team leadership to ensure scalable and high-quality data solutions. Experience : - 9 - 10 years of experience in data engineering / data platforms - Mandatory experience in Pharmaceutical / Life Sciences domain Key Responsibilities : 1. Data Engineering & Platform Development : - Design, build, and manage scalable data pipelines for structured and unstructured data - Develop and maintain ETL/ELT processes for data ingestion, transformation, and integration - Work with data lakes, warehouses, and modern data platforms to enable analytics and AI use cases - Ensure high data quality, performance optimization, and reliability of data systems 2. Data Architecture & Solutioning : - Collaborate with architects to implement data architecture strategies aligned to business needs - Support development of AI/ML-ready data ecosystems - Build reusable data frameworks and accelerators for analytics use cases 3. Pharma Data & Domain Expertise : - Work with pharma datasets across Commercial & Omnichannel analytics - Apply domain business rules, data transformations, and compliance standards 4. Data Governance & Compliance : - Ensure adherence to data governance, security, and compliance standards - Support implementation of regulatory requirements such as GxP, HIPAA, GDPR - Maintain metadata, lineage, and data quality frameworks 5. Stakeholder Collaboration : - Work closely with analytics, reporting, AI/ML, and business teams to gather requirements - Translate business needs into technical data solutions - Support client discussions and provide data-driven recommendations 6. Team Leadership & Delivery : - Lead and mentor a team of data engineers - Manage task allocation, code reviews, and delivery quality - Drive timely and high-quality project execution in a global delivery model 7. Continuous Improvement & Innovation : - Identify opportunities to enhance performance, automation, and scalability - Enable adoption of modern tools and cloud-based data platforms - Contribute to capability building and innovation initiatives. Required Skills : - Strong expertise in Python, SQL, and data engineering frameworks - Hands-on experience with ETL/ELT tools and data pipeline development - Experience working with cloud platforms (AWS / Azure / GCP) - Strong understanding of data lakes, data warehouses, and big data technologies - Knowledge of data modeling and database design - Strong analytical, problem-solving, and debugging skills Preferred Skills : - Exposure to MLOps, AI/ML data pipelines, or GenAI ecosystems - Experience with pharma data vendors (IQVIA, Symphony, Veeva, CRM systems) - Knowledge of data orchestration tools (Airflow, Azure Data Factory, etc.) Leadership & Behavioral Competencies : - Strong ownership and accountability - Effective stakeholder communication - Ability to work in cross-functional, global teams - Proactive, detail-oriented, and solution-driven mindset.