Senior Data Engineer

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

Job summary

Xenon7 is seeking a Senior Data Engineer to own data architecture and platform development for life sciences clients. You will build scalable pipelines spanning genomics, clinical data, and manufacturing datasets in a hybrid Indianapolis setting, collaborating with engineers, scientists, and platform teams.

You will lead ETL/ELT design, enforce governance, and ensure data residency in a regulated environment while advancing analytics, reporting, and ML readiness.

Qualifications

• 10+ years of software development and data platform architecture experience.
• Proven ability to design scalable data pipelines for science/clinical data.
• Experience with regulated life sciences or manufacturing data environments.
• Ability to lead technical discussions with cross-functional teams.
• Strong knowledge of ETL/ELT, governance, and data residency rules.

Responsibilities

• Design and implement production-grade data pipelines and architectures.
• Model and harmonize multi-modal scientific and clinical datasets.
• Collaborate with process engineers and scientists to translate needs into specs.

Skills

Python

PySpark

SQL

Education

Bachelor's or Master’s in Computer Science, Engineering, or related STEM

Tools

Databricks

Snowflake

AWS/Azure

Job description

Location: Indianapolis, IN Metro (Hybrid / 3-Day Onsite) (Open to Regional/EST Candidates with Onsite Travel)

Contract Type: Contractor Full-Time / Enterprise Project Engagement (Outsourced via Xenon7)

About Xenon7

Where elite tech talent meets world-class opportunities! At Xenon7, we work with leading enterprise clients and innovative startups on high-impact projects across Data, AI, Cloud, and Software Engineering. Our expertise in AI solution architecture and specialized technical talent allows us to partner with enterprise leaders on transformative initiatives, driving innovation and business growth.

Job Summary

We are seeking a Senior Data Engineer with extensive experience in data architecture and platform engineering to drive data initiatives for a top-tier life sciences client. This role sits at the critical intersection of scientific research informatics, clinical data systems, and manufacturing process engineering. In this position, you will own the architectural vision and hands-on execution of scalable data platforms and pipelines. You will bridge complex data domains—from small and large molecule research, genomics, and clinical trial datasets to active pharmaceutical ingredient (API) manufacturing processes, batch data, and industrial control systems. Operating in a 3-day onsite hybrid capacity in Indianapolis, you will collaborate directly with process engineers, clinical scientists, and platform teams to build high-performance data infrastructure that accelerates drug discovery and manufacturing operations.

Key Responsibilities

Scientific & Clinical Data Platform Architecture

• Design, build, and maintain production-grade data pipelines and architecture tailored for scientific, clinical trial, and research informatics data (small/large molecule, genomics, proteomics, LIMS)
• Structure complex, multi-modal clinical and scientific datasets to enable advanced analytics, enterprise reporting, and downstream machine learning models

Process Engineering & Manufacturing Integration

• Ingest, harmonize, and model operational technology (OT) and manufacturing process datasets, including API manufacturing pipelines, batch processing data, MES, SCADA, and OSIsoft PI systems
• Unify disparate laboratory and facility data pipelines into centralized, highly available enterprise data platforms

Enterprise Data Engineering & Compliance

• Build robust ETL/ELT pipelines using modern cloud platforms (Databricks, Snowflake, AWS/Azure), PySpark, and SQL
• Ensure all data pipelines and platform integrations strictly adhere to enterprise governance, data residency, and GxP regulatory standards within a heavily monitored environment

Technical Leadership & Domain Alignment

• Partner directly with process engineers, chemical engineering leads, and research informatics directors to translate operational friction into robust technical specifications
• Establish engineering best practices, data modeling standards, and pipeline monitoring frameworks across the enterprise data stack

Requirements

Experience & Mindset

• Experience: Senior-level proficiency (10-20+ years) in software development, data platform architecture, and complex ETL/ELT engineering
• Domain Adaptability: Demonstrated ability to engineer data pipelines across non-standard, highly specialized domains (e.g., transition between process/chemical engineering data and clinical/scientific research informatics)
• Location & Work Auth: Must hold unrestricted US Work Authorization (no sponsorship available) and be able to work 3 days per week onsite in the Indianapolis, IN area
• Culture & Communication: Exceptional problem-solving mindset, strong adaptability, and the ability to articulate complex technical architecture to cross-functional engineering teams

Must-Have Technical Stack

• Languages & Frameworks: Advanced Python, PySpark, and expert-level SQL
• Data Platforms: Hands-on expertise with Databricks, Snowflake, or AWS/Azure enterprise data ecosystems
• Orchestration & ETL: Extensive experience with Airflow, dbt, Spark, and enterprise data orchestration engines
• Data Pipelines: Proven track record building streaming and batch data architectures via REST APIs, message brokers, and database integrations

Domain Competency (Scientific & Process Focus)

• Deep exposure to either scientific/clinical informatics (CDISC/SDTM, LIMS, clinical trials, multi-omics) OR chemical/process engineering data (API manufacturing, batch data, SCADA, MES, OSIsoft PI)

Nice-to-Haves & Certifications

• Academic background in Chemical Engineering, Bio-process Engineering, Computer Science, or a related STEM discipline
• Direct experience working inside regulated GxP environments in the Life Sciences or Specialty Chemicals sectors
• Certifications: Databricks Certified Data Engineer Senior/Professional, Snowflake SnowPro Core/Advanced, or AWS Data Engineer Associate/Professional

What This Role Is NOT

• Not a pure Data Scientist or ML Researcher: You will not be building or training machine learning models; you are designing and scaling the underlying data architecture, pipelines, and platform infrastructure
• Not a non-coding Architect: This is a 100% hands-on engineering lead role requiring direct pipeline construction and technical execution
• Not a Fully Remote Position: This role requires a steady hybrid commitment of 3 days onsite per week at the client site in Indianapolis