Senior Snowflake and AWS Data Engineer

FUJIFILM America is seeking a Senior Data/AI Engineer to design, build, and maintain efficient, scalable data pipelines and architectures that power data products, analytics, and AI-driven solutions. The role involves applying data and AI engineering best practices and collaborating with cross-functional teams to ensure high-quality data solutions that meet business requirements.

Responsibilities:

• Design, build, and maintain enterprise-scale data pipelines on Snowflake Data Platform
• Design, build, and maintain cloud-native AI/ML solutions (AWS, Azure) that support advanced analytics and decision making
• Implement best practices for data quality, observability, lineage, and governance
• Ensure integration of biotech systems (MES, LIMS, SCADA, ERP, QMS) into centralized data platform
• Collaborate with product managers, product engineers, platform architects, and business stakeholders to align data and AI engineering solutions with business requirements
• Support modern AI capabilities, including model deployment, monitoring, and data readiness
• Optimize data platform for performance, scalability, and cost efficiency
• Partner with cybersecurity and compliance teams to ensure adherence to GxP, FDA 21 CFR Part 11, and data privacy regulations
• Promote engineering best practices, including CI/CD, testing, documentation, and peer reviews
• Stay current with emerging technologies (data mesh, real-time streaming, digital twins, generative AI platforms) and introduce relevant innovations

Requirements:

• Bachelor's degree in Computer Science, Data Engineering, AI/ML Engineering, or related field
• 7+ years of professional experience in data engineering, AI/ML engineering, or cloud platform engineering
• Hands-on experience designing and developing data solutions on Snowflake, including data modelling, performance optimization, and cost-efficient usage
• Experience building and maintaining data pipelines using modern frameworks (e.g. Airflow, dbt)
• Experience with Airflow or similar orchestration tool
• Experience with Docker/Kubernetes for container orchestration, monitoring, and lifecycle management
• Experience with modern AI technologies, including LLMs, embeddings, and vector databases
• Strong SQL skills and experience with data modelling for analytics and AI use cases
• Strong experience with cloud platforms (AWS, Azure)
• Proven experience delivering production-grade data solutions
• Familiarity with biotech or life sciences systems and regulatory compliance frameworks (GxP, FDA, EMA)
• Design and implementation of scalable batch and streaming data pipelines
• Strong programming proficiency in Python and SQL/dbt for data processing, automation, and analytics
• Containerization and deployment of data and AI workloads using Docker
• Orchestration and operation of containerized workloads using Kubernetes
• Data quality management, observability, lineage, and governance
• Knowledge of biotech IT/OT systems (MES, LIMS, SCADA), and compliance frameworks (GxP, FDA, data privacy)
• Strong problem-solving, optimization, and troubleshooting skills for large-scale data systems
• Effective communication with both technical and non-technical stakeholders, influencing at senior levels
• Passion for emerging technologies, continuous improvement, and building innovative engineering cultures