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Role Description

The Principal Data/AI Engineer helps drive the technical strategy and architecture of enterprise-scale data and AI platforms that power mission-critical data products, analytics, and AI-driven solutions. In this role, you will operate as a technical expert in planning, designing, developing, and debugging new and existing data pipelines. You will 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 mentor junior engineers through design guidance, code reviews, pairing, and enabling Agile frameworks to promote iterative delivery and continuous improvement.

You will work closely with a cross-functional team of business and IT peers and are expected to lead by example, balancing delivery speed of new features with long-term platform health and technical excellence.

What you'll do:

• Architect, build, and maintain highly scalable batch and streaming pipelines on the Snowflake Data Platform (Snowpipe, Tasks, Streams, Dynamic Tables, Snowpark, Iceberg).
• Architect and deliver ML/GenAI solutions using managed cloud services (AWS, Azure, Snowflake Cortex).
• Implement modern data modeling and architecture patterns; establish and enforce standards for data quality (tests, expectations, SLAs/SLOs), observability (metrics, logs, traces), and lineage.
• 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.
• Enable modern AI use cases - feature stores, vector search/RAG, model serving, safety/guardrails, and continuous monitoring for drift, bias, and performance.
• Optimize storage tiers, compute clusters/warehouses, caching, and workload orchestration for latency and throughput.
• Partner with cybersecurity and compliance teams to ensure adherence to GxP, FDA 21 CFR Part 11, and data privacy regulations.
• Lead design reviews, incident postmortems, and cross-team architecture forums.
• Stay current with emerging technologies (data mesh, real-time streaming, digital twins, generative AI platforms) and introduce relevant innovations.
• And other job duties that may be assigned from time to time.

Qualifications

• Bachelor’s degree in Computer Science, Data Engineering, AI/ML Engineering, or related field.
• 12+ years of professional experience in data/software engineering, AI/ML engineering, or cloud platform engineering.
• Proven experience using Python and SQL.
• Extensive experience building and maintaining data pipelines using modern frameworks (e.g. Airflow, dbt).
• Proven 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).

Preferred Experience and Education

• Advanced degree (MS/PhD) preferred.
• Relevant industry certifications (e.g., Snowflake, AWS, Azure) preferred.

Knowledge, Skills and Abilities

• Design and implementation of scalable batch and streaming data pipelines.
• Strong proficiency in Python and SQL/dbt for data processing, automation, and analytics.
• Extensive experience in Airflow or similar orchestration tool.
• Expertise in designing and developing data solutions on Snowflake, including data modelling, performance optimization, and cost-efficient usage.
• Experience with modern AI technologies, including LLMs, embeddings, and vector databases.
• Proven track of delivering cloud-based solutions (AWS, Azure).
• 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.

Salary and Benefits

The US salary range for this position is $146,000 to $241,000. Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience.

• Robust benefits package including medical, dental, vision and prescription drug coverage with the option of a Health Savings Account with company contributions.
• Industry leading 401(k) savings plan.
• Insurance coverage.
• Employee assistance programs and various wellness incentives.
• Paid vacation time, sick time, and company holidays.