Senior Data Platform Engineer – Life Sciences (Hybrid)

Xenon7; West Lafayette (IN); Hybrid; USD 140,000 - 210,000; Full time

Job summary

Xenon7 seeks a Senior Data Engineer to lead data platform architecture and scalable pipelines for a life sciences client. You will own the architectural vision, partnering with process engineers, scientists, and platform teams to accelerate drug discovery and manufacturing operations.

The role requires 10–20+ years in data engineering, hands-on experience with Databricks, Snowflake, and cloud ETL tools, and a strong governance mindset in a regulated environment.

Qualifications

• Senior-level proficiency (10–20+ years) in software development, data platform architecture, and complex ETL/ELT engineering.
• Experience engineering data pipelines across non-standard domains (process/chemical engineering data and clinical/scientific informatics).
• US work authorization (no sponsorship) and ability to work 3 days onsite weekly in Indianapolis.

Responsibilities

• Design, build, and maintain production-grade data pipelines and architecture for scientific, clinical trial, and research informatics data.
• Ingest, harmonize, and model OT and manufacturing datasets, including API pipelines, batch data, MES, SCADA, and OSIsoft PI systems; unify lab and facility data.
• Build ETL/ELT pipelines on modern cloud platforms (Databricks, Snowflake, AWS/Azure) with PySpark and SQL; enforce governance and data residency in regulated environments.
• Collaborate with process engineers and scientists to translate requirements into robust data specifications and scalable infrastructure.

Skills

Python

PySpark

SQL

Databricks

Snowflake

AWS/Azure

Airflow

dbt

Spark

REST APIs

Messaging systems

Education

Chemical Engineering

Bioprocess Engineering

Computer Science

Tools

Databricks Certified Data Engineer Senior/Professional

Snowflake SnowPro Core/Advanced

AWS Data Engineer Associate/Professional

Job description

Xenon7 seeks a Senior Data Engineer to lead data platform architecture and scalable pipelines for a life sciences client. You will own the architectural vision, partnering with process engineers, scientists, and platform teams to accelerate drug discovery and manufacturing operations.

The role requires 10–20+ years in data engineering, hands-on experience with Databricks, Snowflake, and cloud ETL tools, and a strong governance mindset in a regulated environment.