Description

Lead the architecture and development of large-scale data platforms in regulated healthcare and pharma environments.

Responsibilities

• Define platform roadmaps, solution designs, and technical evaluation guidelines for tech stack finalization.
• Develop data ingestion, orchestration, and migration strategies using Apache Spark, PySpark, and AWS Redshift.
• Design data models to reduce system complexity, improve efficiency, and lower operational costs.
• Implement data governance, access control, and security frameworks including Privacera, Apache Ranger, and Okta.
• Review code, establish coding standards, and guide best practices for data validation and CI/CD pipelines.

Required Skills

• 12+ years of experience in data engineering architecture for enterprise-scale platforms.
• Strong proficiency in Python, SQL, and PySpark for data processing and transformation.
• Hands-on experience with AWS Redshift, EMR, Databricks, and Apache Airflow.
• Knowledge of data virtualization tools such as Dremio.
• Familiarity with search and discovery platforms like Solr, Elasticsearch, or Looker.
• Understanding of DevOps practices including Jenkins, Git, Docker, and Kubernetes.
• Experience with machine learning pipelines and their integration into data platforms.

Preferred Skills

• Proven track record designing enterprise data platforms in healthcare, pharma, or other regulated industries.

Key Skills

Education

Any Graduate