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# Senior Data Engineer, Snowflake & AWS

- **Company:** Fujifilm Holdings America Corporation
- **Location:** Atlanta, GA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $120,000.0 - $198,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Data Analysis, Automation of Tests, Microsoft Azure, Big Data, Cloud Computing, Computer Programming, Continuous Integration, Data Validation, Information Engineering, Data Infrastructure, Data Systems, Database Queries, Supervisory Control and Data Acquisition (SCADA), Infrastructure as a Service (IaaS), Python (Programming Language), Laboratory Information Management Systems, Machine Learning, Performance Tuning, SQL Databases, Data Streaming, Digital Twin, Data Processing, Cloud Platform System, Large Language Models, Snowflake, Generative AI, Containerization, Kubernetes, Information Technology, Software Version Control, Data Pipelines, GXP, Docker
- **Published:** August 16, 2026
- **Apply:** https://www.atlantacareerpath.com/job.asp?id=3355993553&tx=FL104LFU&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* 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).

Knowledge, Skills and Abilities:

 * 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.

## Description

The Senior Data/AI Engineer is responsible for designing, building, and maintaining efficient, scalable data pipelines and architectures that power data products, analytics, and AI-driven solutions. In this role, you will apply and advocate for data and AI engineering best practices, including idempotent modular pipeline design, version control, automated testing, CI/CD, IaaS, data quality checks and observability. You will help establish and continuously improve standards for how data and AI solutions are designed, built, deployed, and operated in production. You will work closely with cross-functional team of business and IT peers and expected to lead by example - balancing delivery speed of new features with long-term platform health and technical excellence., * 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.


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