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Senior Data Engineer

12 hours, 51 minutes ago
United States
Full-time
Lead
Data Engineer
Software Development
Apache Airflow Apache Spark AWS Databricks Generative AI Machine Learning SQL
Apply Now
Tiger Analytics

Tiger Analytics

Tiger Analytics is a leading advanced analytics consulting firm partnering with Fortune 100 companies to drive business value through expertise in marketing science, customer analytics, and operations analytics.

Professional Services
1K-5K
Founded 2011
View All Jobs 75

Description

  • Design, develop, and deploy end-to-end data pipelines on AWS using S3, Glue, Lambda, Redshift, and related technologies.
  • Build and optimize scalable data processing workflows with Databricks, Apache Spark, and SQL.
  • Develop and maintain Apache Airflow workflows for orchestration, scheduling, monitoring, and automation.
  • Integrate and process commercial pharmaceutical data sources, including Xponent, Veeva, MMIT, Plantrak, Specialty Pharmacy, and LAAD.
  • Build pipelines supporting pharmaceutical KPIs, metrics, analytics, and reporting.
  • Design data pipelines for AI/ML and Generative AI workloads, including structured and unstructured data preparation.
  • Support LLM applications, vector embeddings, and knowledge retrieval/RAG solutions.
  • Migrate legacy data systems and pipelines to AWS cloud and lakehouse architectures.
  • Monitor, troubleshoot, and optimize pipelines for performance, reliability, scalability, data quality, and cost.
  • Collaborate with technical and business stakeholders to translate pharmaceutical requirements into scalable data solutions.

Requirements

  • 8+ years of experience in data engineering, preferably in commercial pharmaceutical or healthcare data environments.
  • Strong hands-on experience with AWS, Databricks, Apache Spark, and SQL.
  • Experience building ETL/ELT pipelines and large-scale data processing workflows.
  • Hands-on experience with Apache Airflow orchestration.
  • Strong understanding of data modeling, data lake/lakehouse architecture, ingestion, and transformation frameworks.
  • Deep knowledge of commercial pharmaceutical data sources, including Xponent, Veeva, MMIT, Plantrak, Specialty Pharmacy, and LAAD.
  • Understanding of pharmaceutical commercial data processes such as alignment, allocation, split credits, market basket, and customer universe.
  • Strong understanding of pharmaceutical KPIs, metrics, and commercial analytics.
  • Strong analytical, problem-solving, and data troubleshooting skills.

Benefits

  • Career development opportunities as the company grows.
  • Opportunity to work in a small, entrepreneurial environment.
  • High degree of individual responsibility and ownership.

Interested in this position?

Apply directly on the company website

Apply Now

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