Cloud Architect (AWS) - Life science

Role: Data Engineer / Data Integration (AWS) - Life Science Domain Experience: 8+ Years Location: REMOTE JD:

Role Summary We are looking for a highly skilled

Lead Data Architect / Technical Lead who can design, build, and manage enterprise data integration solutions across multiple source systems. The candidate should have strong experience in handling large-scale data pipelines related to

commercial and expense data in the

Life Sciences industry . The ideal candidate should be capable of leading technical teams, architecting scalable solutions, and driving end-to-end delivery using modern cloud and integration technologies.

Key Responsibilities

• Design and implement data pipelines to ingest, transform, and integrate data from multiple enterprise source systems.
• Build scalable data engineering solutions using Databricks and cloud platforms.
• Integrate data across systems such as Salesforce, Vault, expense management platforms, and other enterprise applications.
• Design secure API-based integrations between systems.
• Perform data modeling, transformation, cleansing, and optimization for analytics and downstream consumption.
• Design architecture for batch and near real-time data processing.
• Lead technical discussions, solution design, and architecture reviews.
• Collaborate with business stakeholders to understand commercial reporting and analytics requirements.
• Mentor developers and lead large technical teams.
• Ensure best practices for CI/CD, deployment, monitoring, security, and performance optimization.
• Explore AI-driven capabilities such as Agentic AI for intelligent workflow automation.

Required Skills Technical Skills

• Strong experience in

Data Engineering / Data Integration (8+ years preferred)

• Hands-on expertise in:
• Amazon Web Services including:
• S3, Glue, Lambda, API Gateway, IAM, CloudWatch
• Good understanding of VPC/networking concepts (private/public subnets, security groups, private endpoints)
• Databricks (PySpark, Delta Lake, Medallion architecture)
• MuleSoft
• Salesforce
• Veeva Vault
• Strong knowledge of:
• Python / PySpark
• SQL
• ETL / ELT pipelines
• Data modeling
• API integrations (REST, OAuth, JWT)
• CI/CD pipelines
• Git-based deployment workflows

Domain Skills

• Strong understanding of

Life Sciences commercial domain

• Experience handling datasets related to:
• HCP / HCO data
• Commercial operations
• Field activity / CRM data
• Expense management
• Sales performance analytics
• Compliance-related data

Preferred Skills

• Experience in

Agentic AI / AI Agents

• Knowledge of ML model integration in Databricks
• Experience with GenAI / RAG-based solutions
• Solution architecture experience for enterprise-scale systems

Leadership Expectations

• Ability to lead and architect large teams
• Strong stakeholder communication
• Ability to drive design decisions independently
• Strong problem-solving and decision-making skills

Candidate Profile We are

not looking for a pure ETL developer or only a data engineer . We need someone who can operate as a:

• Data Architect
• Integration Lead
• Domain SME (Life Sciences Commercial)
• Technical Leader with AI awareness