Senior Data Engineer

Location and Engagement

• The role is based in the Indianapolis, Indiana metro area with a hybrid schedule of three onsite days per week.
• Regional or Eastern Time candidates may be considered if they can travel onsite.
• This is a full-time contractor enterprise project engagement outsourced through Xenon7.

Job Summary

Scientific and Clinical Data Platform Architecture

• Design, build, and maintain production-grade pipelines and architecture for scientific, clinical trial, and research informatics data.
• Work with small- and large-molecule research, genomics, proteomics, LIMS, and clinical datasets.
• Structure multi-modal datasets for analytics, reporting, and downstream machine learning.

Manufacturing Data Integration

• Ingest, harmonize, and model operational technology and manufacturing process datasets.
• Work with API manufacturing pipelines, batch processing data, MES, SCADA, and OSIsoft PI systems.
• Unify laboratory and facility data pipelines into centralized, highly available enterprise platforms.

Enterprise Data Engineering

• Build ETL/ELT pipelines using Databricks, Snowflake, AWS or Azure, PySpark, and SQL.
• Ensure pipelines and integrations comply with enterprise governance, data residency, and GxP standards.
• Establish data-modeling standards, engineering best practices, and pipeline-monitoring frameworks.

Required Experience

• Bring senior-level proficiency with 10–20+ years in software development, data platform architecture, and complex ETL/ELT engineering.
• Engineer pipelines across specialized scientific, clinical, chemical, or process engineering domains.
• Use advanced Python, PySpark, and expert-level SQL.
• Have experience with Airflow, dbt, Spark, data orchestration engines, REST APIs, message brokers, and database integrations.
• Have deep exposure to either scientific or clinical informatics, or chemical and process engineering data.

Preferred Qualifications

• A STEM academic background in Chemical Engineering, Bio-process Engineering, Computer Science, or a related field is preferred.
• GxP experience in life sciences or specialty chemicals is preferred.
• Databricks, Snowflake, or AWS data engineering certifications are preferred.

Role Scope

• This is a hands-on engineering lead role requiring direct pipeline construction and technical execution.
• The role is not focused on training machine learning models and is not fully remote.