Director, Analytics Engineering
Novartis
Summary
Novartis has an exciting opportunity for a Director, Analytics Engineering. This role is responsible for building next-generation, AI-powered automated data pipelines and scalable data repositories that enable enterprise data science and analytics at scale. By leveraging advanced AI technologies, modern data engineering tools, and feature engineering platforms, this director creates self-service, analytics-ready datasets and enterprise feature stores that empower both expert data scientists and citizen data scientists to rapidly develop, deploy, and scale models.
Job description
This position can be based remotely anywhere in the U.S. (there may be some restrictions based on legal entity). This role would not provide relocation. This position will require 20% travel. There are 2 positions available.
Major accountabilities
- Design and implement intelligent, self-healing data pipelines that leverage AI/ML for automated data quality monitoring, anomaly detection, and remediation.
- Build and maintain centralized feature stores that enable feature reusability across multiple models and use cases.
- Create curated data repositories optimized for data science/AI workflows, including training datasets, evaluation datasets, and production serving layers.
- Develop automated feature engineering pipelines that transform raw data into analytics-ready features with lineage tracking.
- Partner with Enterprise IT to optimize analytics platform architecture for high-performance data science workloads.
- Build automated pipelines that integrate diverse data sources including sales, CRM, patient claims, real-world evidence, and unstructured data.
- Create self-service data access layers that empower data scientists and analysts to query and extract data independently.
- Establish SLAs for data availability, freshness, and quality; implement monitoring and observability solutions.
Essential Requirements
- Advanced degree in Computer Science, Data Engineering, or related field.
- 7+ years of experience in data engineering, ML/AI engineering, or analytics infrastructure.
- 5+ years leading teams building enterprise-scale data platforms and feature stores.
- Expert knowledge of feature store technologies (Feast, Tecton, SageMaker Feature Store, Databricks Feature Store).
- Deep expertise in modern data platforms optimized for ML workloads (Databricks, Auto ML, Snowflake, BigQuery).
- Strong proficiency in Python, SQL, Spark/PySpark for large-scale data processing.
- Experience with data orchestration tools (Airflow, Prefect, dbt) and CI/CD for data pipelines.
- Understanding of data governance, privacy (HIPAA, GDPR), and compliance in life sciences.
Preferred Qualities
- Proven track record of implementing AI/ML-powered automation in data engineering workflows.
- Strategic thinker who can balance innovation (cutting-edge AI tools) with reliability (production stability).
- Builder mindset with ability to create scalable, self-service capabilities that reduce dependency on data engineering.
- Experience in pharmaceutical, healthcare, or life sciences industry.
- Knowledge of streaming technologies, MLOps tools, and data lakehouse architecture.
Requirements
- Advanced degree in Computer Science, Data Engineering, or related field
- 7+ years of experience in data engineering, ML/AI engineering, or analytics infrastructure
- 5+ years leading teams building enterprise-scale data platforms and feature stores
- Expert knowledge of feature store technologies (Feast, Tecton, SageMaker Feature Store, Databricks Feature Store)
- Deep expertise in modern data platforms optimized for ML workloads (Databricks, Auto ML, Snowflake, BigQuery)
- Strong proficiency in Python, SQL, Spark/PySpark for large-scale data processing
- Experience with data orchestration tools (Airflow, Prefect, dbt) and CI/CD for data pipelines
- Understanding of data governance, privacy (HIPAA, GDPR), and compliance in life sciences
Benefits
- Health insurance
- Life insurance
- Disability benefits
- 401(k) with company contribution and match
- Vacation
- Personal days
- Holidays
- Annual equity awards
- Performance-based cash incentive
Company overview
Novartis is a global pharmaceutical company headquartered in Basel, Switzerland, dedicated to reimagining medicine to improve and extend people's lives. As an innovative medicines company, Novartis focuses on developing high-value treatments that address society's greatest disease burdens through technology leadership in research and development. The company operates across five core therapeutic areas: cardiovascular, renal and metabolic diseases; immunology; neuroscience; oncology; and hematology. With a workforce of approximately 75,883 employees worldwide, Novartis reaches nearly 300 million patients across 118 countries. The company leverages advanced technology platforms including targeted protein degradation, cell therapy, gene therapy, radioligand therapy, and xRNA to develop breakthrough treatments. Novartis maintains a strong portfolio of oncology drugs and generics while continuously expanding its pipeline through strategic acquisitions and internal research. The company's commitment extends beyond drug development to ensuring global access to medical innovations through novel access approaches and patient assistance programs.