Director Analytics Infrastructure, Pipeline Operations

Novartis

East Hanover, NJ, US
Base: $194,600 - $361,400 py; bonus/equity: perfor...
Hybrid
Ai-powered automated data pipelines
Enterprise feature store technologies
Modern data platforms for ml workloads
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

Job Summary

  • 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.
  • The position requires designing intelligent, self-healing data pipelines leveraging AI/ML for automated data quality monitoring, anomaly detection, and remediation.
  • Employees are eligible for a comprehensive benefits package including health, life and disability benefits, 401(k) with company match, performance-based incentives, and generous time off.

Matching Summary

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.

Salary

Base: $194,600 - $361,400 per year; Bonus/Equity: Performance-based cash incentive and eligibility for annual equity awards; Benefits: Health, life, disability, 401(k) with match, generous time off

Skills & Requirements

Must-have

  • AI-powered automated data pipelines
  • Enterprise feature store technologies
  • Modern data platforms for ML workloads
  • Python, SQL, Spark/PySpark proficiency
  • Data orchestration and CI/CD tools
  • Data governance and compliance

Nice-to-have

  • AI/ML-powered automation in data workflows
  • Strategic thinker balancing innovation and stability
  • Builder mindset for scalable self-service capabilities
  • Experience in pharmaceutical or healthcare industry
  • Knowledge of streaming technologies and MLOps
  • Data lakehouse architecture knowledge

Key Requirements

  • Advanced degree in Computer Science or related field
  • 10+ years experience in data engineering or analytics infrastructure
  • 5+ years leading enterprise-scale data platform teams
  • Expertise with feature store technologies (Feast, Tecton, SageMaker, Databricks)
  • Proficiency in Python, SQL, Spark/PySpark
  • Experience with Airflow, Prefect, dbt and CI/CD
  • Understanding of HIPAA, GDPR and life sciences compliance
  • Ability to travel up to 15%

Work Rights

Not specified

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