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Biotech Data Analyst Jobs (NOW HIRING)

Stellar IT Group

BioTech Data Engineer

Saint Louis, MO · On-site

$111K - $133K/yr

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 ...

Empower Professionals

Data Analyst

Hopewell, NJ · On-site

Experience with pharma, biotech, or life sciences data, along with strong analytical skills and high attention to detail and accuracy. * Ability to analyze, model, and interpret data including ...

New

CAREERS | vector

Data Analyst

Washington, DC · Hybrid

... biotech, advanced semiconductors, material characterization). * Working proficiency in R for ... Familiarity with supply chain analytics, trade data (Panjiva, ImportGenius, UN Comtrade), corporate ...

Vector Resources, Inc

Data Analyst

Washington, DC · On-site

$100K - $150K/yr

... biotech, advanced semiconductors, material characterization). * Working proficiency in R for ... Familiarity with supply chain analytics, trade data (Panjiva, ImportGenius, UN Comtrade), corporate ...

Vector Resources, Inc

Data Analyst

Washington, DC · On-site

$100K - $150K/yr

... biotech, advanced semiconductors, material characterization). * Working proficiency in R for ... Familiarity with supply chain analytics, trade data (Panjiva, ImportGenius, UN Comtrade), corporate ...

Freseniusglobal

Senior Data Analyst

Lake Zurich, IL · On-site

$104K - $110K/yr

Master's degree is a plus. * 3+ years of experience in data analysis, preferably in the life sciences, biotech, or healthcare sector. * Strong experience with data visualization tools (e.g., Tableau ...

SYNTEGON

Master Data Analyst

New Richmond, WI

... biotech, and food industries. With seamless processes, innovative technologies, and sustainable ... As our Master Data Analyst , you'll own the integrity and structure of material master data across ...

Belcan

Material Master Data Analyst

Saint Louis, MO · On-site

$39.58/hr

Material Master Data Analyst Location: Saint Louis, MO ZIP Code: 63146 Start Date: Right Away ... Knowledge of breeding, agriculture, and/or biotechnology * Experience in ERP data governance, data ...

SYNTEGON

Master Data Analyst

New Richmond, WI

$80K/yr

... biotech, and food industries. With seamless processes, innovative technologies, and sustainable ... As our Master Data Analyst , you'll own the integrity and structure of material master data across ...

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Biotech Data Analyst information

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$34K

$82.6K

$136K

How much do biotech data analyst jobs pay per year?

As of Jun 11, 2026, the average yearly pay for biotech data analyst in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.

What are typical daily responsibilities for a Biotech Data Analyst?

A typical day for a Biotech Data Analyst involves collecting, cleaning, and analyzing large datasets from biological experiments or laboratory studies. You may use statistical and data visualization tools to identify trends, interpret results, and prepare reports or presentations for scientific and cross-functional teams. Collaboration with researchers, laboratory staff, and software engineers is common to ensure the data supports ongoing projects and regulatory requirements. Additionally, you may stay current on advances in analytical methods to improve workflows and contribute to innovative research initiatives.

What does a Biotech Data Analyst do?

A Biotech Data Analyst collects, processes, and interprets biological and clinical data to support research and decision-making in biotechnology and healthcare. They work with large datasets, applying statistical and machine learning techniques to uncover insights that drive innovation in drug development, genetics, and biomedical research. Their role often involves data visualization, database management, and collaboration with scientists and engineers. Strong analytical skills and proficiency in tools like Python, R, and SQL are essential for success in this role.

What are the key skills and qualifications needed to thrive in the Biotech Data Analyst position, and why are they important?

To thrive as a Biotech Data Analyst, you need a strong background in biological sciences, statistics, and data analysis, often supported by a degree in bioinformatics, biotechnology, or a related field. Familiarity with software tools such as Python, R, SQL, and bioinformatics platforms, as well as experience using data visualization and statistical analysis software, is typically required. Strong attention to detail, effective communication, and problem-solving abilities set top candidates apart. These skills are essential for interpreting complex biological data, ensuring accurate results, and clearly conveying findings to research teams or stakeholders.

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Biotech Data Analyst jobs near you

BioTech Data Engineer

Stellar IT Group

Saint Louis, MO • On-site

$111K - $133K/yr

Full-time

Posted 8 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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