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Biotech Data Architect Jobs (NOW HIRING)

Stellar IT Group

BioTech Data Engineer

Saint Louis, MO · On-site

$111K - $133K/yr

Biotech Data Engineer Job Type: FTE Work Mode: Remote The Biotech Data Engineer focuses on ... Architect and implement data integration frameworks across diverse Adtech and Martech ecosystems ...

NAVA Software Solutions

Data Architect - Remote

Parsippany, NJ · On-site +1

$64 - $82.50/hr

Industry experience (Pharma/Biotech) is a MUST. Job Function: The Data Architect is a role for a BioPharma client building a Data Warehouse. The Data Architect will be responsible for designing and ...

Lawrence Harvey

Manufacturing Data Architect

Dallas, TX · On-site

$180K - $220K/yr

Manufacturing Data Architecture Lead $180-220k base salary + 20% bonus Hybrid - Dallas, TX ... BioTech * Good understanding of manufacturing systems & automation (PLCs, SCADA, MES, ERPs and ...

Kanak Elite Services Inc

Lead Data Architect Work Location : Hybrid Summary * 13+ years Experience * Skilled with: Oracle ... Perfect Communication * Preferred: (medical device or biotech industry) SO/FDA regulated ...

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Biotech Data Architect information

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$10

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How much do biotech data architect jobs pay per hour?

As of Sep 10, 2026, the average hourly pay for biotech data architect in the United States is $69.98, according to ZipRecruiter salary data. Most workers in this role earn between $61.30 and $78.85 per hour, depending on experience, location, and employer.

What is a Biotech Data Architect?

A Biotech Data Architect is a specialized professional who designs, manages, and optimizes data systems for biotechnology organizations. They create the infrastructure to store, integrate, and analyze large volumes of biological and clinical data, ensuring data integrity and security. Their work enables researchers and scientists to access and use data efficiently for drug discovery, genomics, and other biotech applications. Biotech Data Architects collaborate closely with IT teams, scientists, and regulatory experts to meet industry-specific requirements.

What are the key skills and qualifications needed to thrive as a Biotech Data Architect?

To thrive as a Biotech Data Architect, you need expertise in data modeling, database design, and a background in life sciences or bioinformatics, often supported by a degree in computer science, biology, or a related field. Familiarity with technologies such as SQL, NoSQL databases, cloud platforms (e.g., AWS, Azure), and data integration tools, as well as certifications in data architecture, are typically required. Strong analytical thinking, problem-solving, and the ability to communicate complex technical concepts to interdisciplinary teams are key soft skills. These competencies ensure effective management and integration of complex biological datasets, supporting innovation and data-driven decision-making in biotech organizations.

How does a Biotech Data Architect typically collaborate with scientists and IT teams to design effective data solutions?

A Biotech Data Architect plays a pivotal role in bridging the gap between scientific research teams and IT professionals. They work closely with scientists to understand experimental workflows, data types, and analysis requirements, ensuring that data models and infrastructure support accurate, reproducible research. At the same time, they partner with IT teams to implement robust databases, data pipelines, and security measures that comply with industry standards. Effective communication and interdisciplinary collaboration are essential, as the architect must translate scientific needs into technical specifications and vice versa.

What is the difference between Biotech Data Architect vs Bioinformatics Data Analyst?

AspectBiotech Data ArchitectBioinformatics Data Analyst
CredentialsBachelor's or Master's in Bioinformatics, Data Science, or related fields; certifications in data management or cloud platformsBachelor's or Master's in Bioinformatics, Biology, or related fields; certifications in data analysis tools
Work EnvironmentDesigning data infrastructure in biotech companies, research labs, or pharmaceutical firmsAnalyzing biological data sets in research projects, biotech firms, or academic institutions
Employer & Industry UsageUsed by biotech and pharmaceutical companies to develop data systemsUsed by research teams and labs to interpret biological data

The Biotech Data Architect focuses on designing and managing data infrastructure within biotech organizations, ensuring data is accessible and secure. In contrast, the Bioinformatics Data Analyst primarily interprets biological data to support research and development. Both roles require strong data skills but differ in scope and responsibilities.

What are popular job titles related to Biotech Data Architect jobs?

For Biotech Data Architect jobs, the most frequently searched job titles are:

Infographic showing various Biotech Data Architect job openings in the United States as of September 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $145,556 per year, or $70 per hour.

BioTech Data Engineer

Saint Louis, MO • On-site

Stellar IT Group
See more jobs at Stellar IT Groupexternal

$111K - $133K/yr

Full-time

Re-posted 10 days ago

Job description

Overview:
Job Title: Biotech Data Engineer
Job Type: FTE
Work Mode: Remote
The Biotech Data Engineer focuses on designing, building, and maintaining scalable Azure Databricks-based data pipelines and architectures that enable analytics, AI/ML, and reporting across commercial functions. It involves leading data engineering initiatives, ensuring governance and compliance, optimizing performance and costs, and collaborating across teams to advance the company's data and AI strategy. The role reports to the Director of Business Intelligence.
Roles & Responsibilities
  • Design, build, and maintain scalable, reliable, and cost-efficient data pipelines using Azure Databricks in support of analytics, machine learning, data science, and operational use cases
  • Lead data engineering initiatives that enable AI/ML model development, LLM integrations, and AI-driven applications while ensuring scalability and alignment with enterprise and business priorities
  • Architect and implement data integration frameworks across diverse Adtech and Martech ecosystems, incorporating Google Analytics, media campaign data, and third-party marketing APIs like Salesforce
  • Manage and optimize data ingestion, transformation, and storage processes using SQL, Python, and PySpark to integrate structured and unstructured data sources
  • Design and maintain API integrations with internal and external systems, including Python- and PySpark-based services and AI/LLM-powered APIs for advanced analytics and automation
  • Administer and maintain Azure-based data tools and platforms (e.g., Databricks, ADF) to ensure operational excellence, reliability, and security
  • Collaborate with internal stakeholders and external partners to evolve data platform design and architecture that supports advanced analytics, personalization, marketing intelligence, and marketing automation
  • Execute against the company's data and AI strategy by translating strategic goals into technical architecture, design and requirement documents, and implementation roadmaps
  • Ensure data quality, integrity, and consistency through robust validation, monitoring, and alerting mechanisms within Azure Databricks
  • Implement and enforce data governance, security, and compliance standards in collaboration with IT, InfoSec, and data governance teams
  • Partner with analytics, marketing, commercial operations, and core technology/cybersecurity teams to deliver fit-for-purpose commercial data products
  • Monitor and optimize data infrastructure costs, performance, and scalability across Azure cloud environments
  • Develop and maintain architecture documentation, pipeline specifications, and design diagrams for transparency and knowledge sharing with technical and business stakeholders
  • Participate in architecture discussions, design reviews, and CI/CD workflows to ensure high-quality engineering and deployment practices as part of an Agile engineering team
  • Continuously evaluate and recommend new Azure services, designs, improvements, frameworks, and AI integration tools to enhance our data platform
  • Drive automation, observability, and standardization across data workflows to improve efficiency and reduce manual intervention
  • Complete all job duties in compliance with company policy, SOPs, safety rules, and applicable federal, state, and local regulations

Education & Licenses And Experience
Bachelor of science degree required. A minimum of 5 years transferable working experience in the area of operational support of a Data Engineering, Data Architecture, or Cloud Platforms function preferred. The ideal candidate will have recent and relevant experience in the pharma or biotech industry.
Required Competencies & Skills
  • Experience with Azure Cloud (Databricks, DevOps, DataFactory)
  • Pharma / biotech domain experience, specifically within the commercial data space (sales, market access / payer, marketing)
  • Strong hands-on python, pyspark, and SQL skills
  • Direct experience with building and leveraging API integrations in ETL pipeline development
  • Experience integrating with current best-in-class AI models and APIs like OpenAI API, Databricks AI models, etc.
  • Self-driven with ability to independently design end-to-end data pipelines while ensuring architectural best practices
  • Ability to collaborate with a broad set of stakeholders to evaluate the business need and construct a technical design that can enable stakeholder priorities
  • Travel up to 20%

Preferred Competencies & Skills
  • Strong knowledge of and experience with maximizing business value using Databricks Unity Catalog or Databricks One capabilities
  • Familiarity with tools and practices in the Martech and Adtech landscape
  • Knowledge of Consumer, Patient, or HCP data ecosystems
  • Experience with identity providers like LiveRamp, Acxiom, Experian, etc.
  • Experience with custom-built or third-party Customer Data Platforms (CDP)
  • Experience with marketing automation tools

Skills:
Data Engineering

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