Associate Director, Data Engineering and Architect

About the role

We are seeking an experienced Emerging Data Platform Technologies Architect to drive the design, implementation, and optimization of modern data solutions within Insmed. This role will focus on leveraging cutting-edge cloud technologies, data integration, quality tools, and data platforms to enable scalable, high-performance data ecosystems.

Responsibilities

• Design and implement scalable, secure, and cloud-native data platforms using AWS, GCP, and Snowflake to enhance analytics, AI/ML, and real-time processing capabilities.
• Led the data engineering development including data pipelines framework and ETL workflows leveraging Qlik Talend, Python, advanced SQL, AWS and GCP services.
• Implement serverless architecture and containerization (Docker, Kubernetes).
• Lead AI capabilities development within data platforms, enable AI/ML workflows and ML Ops for advanced analytics and predictive modeling.
• Design and Implement data governance frameworks using tools like Talend ensuring data quality, integrity, lineage, and compliance.
• Develop monitoring and observability strategies and implement them to ensure system reliability, data consistency and reporting accuracy.
• Establish best practices for data modeling, metadata management, and data cataloging. Ensure compliance with biopharma industry regulations (HIPAA, GxP, GDPR, etc.).
• Optimize data operations, streamline data reconciliation by task automation using scripting languages such as Python or JavaScript.
• Monitor and optimize data ingestion, transformation query performance and manage workloads to ensure efficient and cost-effective data processing.
• Develop technology roadmaps aligned with Insmed's R&D, clinical, commercial analytics, and regulatory requirements.
• Collaborate with business stakeholders to understand data needs and translate them into actionable data solutions on Snowflake.
• Drive innovation in data management, integration, and governance frameworks.

Requirements

• A minimum of a Bachelor’s degree in Science, Business or Technology, plus 10+ years of experience in data architecture, cloud computing, and data engineering.
• Expertise in Snowflake, Talend, Qlik, AWS, GCP, and modern data engineering tools.
• Strong background in ETL, data lakes, data warehousing, and streaming architectures.
• Experience in biopharma, life sciences, or healthcare, with knowledge of regulatory compliance is a must.
• Proficiency in SQL, Python, Spark, and cloud-native analytics services.
• Understanding of AI/ML integration and MLOps for data-driven insights.
• Excellent problem-solving and ability to effectively communicate technical concepts to both technical and non-technical stakeholders.

Qualifications

• Nice to have (but not required): Preferred experience with commercial systems like Veeva CRM, Salesforce health cloud.
• Nice to have (but not required): Preferred experience with data visualization tools like Qlik Sense, or similar tools.