Job Description
Must Have
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
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 [Solution A...or Manager | Word]
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 [Solution A...or Manager | Word]
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
Good to have
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 [Solution A...or Manager | Word]
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 [Solution A...or Manager | Word]
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