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# Senior Data Engineer

- **Company:** Tiger Analytics
- **Location:** Chicago, IL, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Data Analysis, Big Data, Cloud Computing, Data Architecture, Information Engineering, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Data Systems, Information Retrieval, Machine Learning, Standard Sql, SQL Databases, Unstructured Data, Data Processing, Data Ingestion, Retrieval-Augmented Generation, Apache Spark, Vector Embeddings, Generative AI, AWS Lambda, Data Lakes, AWS Glue, Data Management, Veeva, Data Pipelines, Amazon Redshift, Databricks
- **Published:** November 2, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-data-engineer-chicago-il--b9f8bc94-e44d-42fe-8c79-bd10e3c48722

## About the Role

Data Science, Machine Learning, Leadership, Consulting, Market Research, Artificial Intelligence (AI), Channel Strategies, Data Management, Cloud Computing, Amazon Web Services (AWS), * 8+ years of experience in Data Engineering, preferably with experience supporting commercial pharmaceutical/healthcare data environments.

 * Strong hands-on experience with AWS cloud, Databricks, Spark, and SQL
 * Strong experience building ETL/ELT data pipelines and large-scale data processing workflows.
 * Hands-on experience with Apache Airflow for workflow orchestration.
 * Strong understanding of data modeling, data lake/lakehouse architecture, data ingestion, and transformation frameworks.
 * Deep knowledge of commercial pharmaceutical data sources: Xponent, Veeva, MMIT, Plantrak, Specialty Pharmacy, LAAD, and other commercial pharma data sources
 * Strong understanding of pharmaceutical commercial data processes, including: Alignment, Allocation, Split credits, Market basket, Customer universe
 * Strong understanding of pharma KPIs, metrics, and commercial analytics.
 * Strong analytical, problem-solving, and data troubleshooting skills.

## Description

We are seeking an experienced Data Engineer to join our data team. In this role, you will be responsible for designing, building, and maintaining scalable data pipelines, data integration processes, and data infrastructure on AWS cloud. You will collaborate closely with data scientists, analysts, and AI teams to support analytics, machine learning, and Generative AI initiatives across the organization., * Design, develop, and deploy end-to-end data pipelines on AWS using services such as Amazon S3, AWS Glue, AWS Lambda, Amazon Redshift, and related data platform technologies.

 * Build and maintain scalable data processing and transformation workflows using Databricks, Apache Spark, and SQL.
 * Develop and maintain Apache Airflow workflows for pipeline orchestration, scheduling, dependency management, monitoring, and automation.
 * Integrate and process commercial pharmaceutical data sources such as Xponent, Veeva, MMIT, Plantrak, Specialty Pharmacy, LAAD, and similar sources.
 * Build and optimize data pipelines supporting pharma KPIs, metrics, analytics, and reporting requirements.
 * Design and implement data pipelines for AI/ML and Generative AI workloads, including structured and unstructured data preparation.
 * Enable data pipelines supporting LLM-based applications, vector embeddings, and knowledge retrieval/RAG solutions.
 * Support migration of legacy data systems and pipelines to modern AWS cloud and lakehouse architectures.
 * Monitor, troubleshoot, and optimize data pipelines for performance, scalability, reliability, and cost-effectiveness.
 * Ensure data pipelines meet required standards for data quality, accuracy, consistency, and operational reliability.
 * Communicate effectively with technical and business stakeholders to understand requirements and translate pharmaceutical business needs into scalable data solutions.