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Biotech Data Management 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 ... Manage and optimize data ingestion, transformation, and storage processes using SQL, Python, and ...

Alkermes

Director, Data Management

Waltham, MA · On-site

$205K - $230K/yr

Minimum 10 years data management (atleast 3 years of supervisory/leadership) experience in a pharmaceutical/biotech setting, CCDM preferred. * Significant experience serving as a Lead Data Manager or ...

The Lotus Group

Director Clinical Data Management

Manhattan, NY · Remote

$88K - $120K/yr

The Lotus Group is partnering with a leading biotech client to hire a Director of Clinical Data Management. This is a senior leadership role reporting into the Head of Biometrics and will function as ...

New

The Lotus Group

Director Clinical Data Management

Manhattan, NY · Remote

$88K - $120K/yr

The Lotus Group is partnering with a leading biotech client to hire a Director of Clinical Data Management. This is a senior leadership role reporting into the Head of Biometrics and will function as ...

New

Alkermes

Director, Data Management

Waltham, MA · Hybrid

$205K - $230K/yr

Minimum 10 years data management (atleast 3 years of supervisory/leadership) experience in a pharmaceutical/biotech setting, CCDM preferred. * Significant experience serving as a Lead Data Manager or ...

Biogen

Manager, Commercial Data Management

Cambridge, MA · On-site

$122K - $163K/yr

Minimum of 3 years of experience in data management, analytics enablement, or related roles within biotech/pharma, healthcare, or consulting * Experience supporting commercial data sources (e.g., CRM ...

Biogen

Manager, Commercial Data Management

Cambridge, MA

$117K - $163K/yr

Minimum of 3 years of experience in data management, analytics enablement, or related roles within biotech/pharma, healthcare, or consulting * Experience supporting commercial data sources (e.g., CRM ...

AskBio

Manager, Data Management

Durham, NC · On-site

Bachelor's degree in life sciences, statistics, biostatistics, mathematics, computer science, biotechnology or related field with a minimum of 6 years' clinical trial related data management ...

Biogen

Manager, Commercial Data Management

Cambridge, MA · On-site

$117K - $163K/yr

Minimum of 3 years of experience in data management, analytics enablement, or related roles within biotech/pharma, healthcare, or consulting * Experience supporting commercial data sources (e.g., CRM ...

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Biotech Data Management information

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$14

$33

$56

How much do biotech data management jobs pay per hour?

As of Sep 1, 2026, the average hourly pay for biotech data management in the United States is $33.07, according to ZipRecruiter salary data. Most workers in this role earn between $24.52 and $39.18 per hour, depending on experience, location, and employer.

What is biotech data management?

Biotech data management refers to the collection, storage, organization, and analysis of large volumes of biological and experimental data generated in biotechnology research and development. This role ensures that data is accurate, accessible, and secure, supporting scientific discoveries and regulatory compliance. Professionals in this field often work with databases, bioinformatics tools, and data governance policies to help researchers make informed decisions and maintain data integrity.

What are the key skills and qualifications needed to thrive in biotech data management?

To thrive in Biotech Data Management, you need a strong background in biology or life sciences, data analysis, and database management, typically supported by a relevant degree. Familiarity with bioinformatics tools, laboratory information management systems (LIMS), and programming languages such as Python or R is commonly required. Attention to detail, problem-solving, and effective communication are vital soft skills for ensuring data integrity and collaboration across teams. These competencies are essential for managing complex scientific data, supporting research accuracy, and driving innovation in biotech environments.

What are some common challenges faced in a biotech data management role, and how can they be addressed?

One of the main challenges in Biotech Data Management is ensuring data integrity and compliance with strict regulatory standards such as FDA or GDPR. Managing large and complex datasets from a variety of laboratory instruments and research studies also requires strong attention to detail and robust data organization skills. Collaboration with scientists, IT professionals, and regulatory teams is essential to maintain accurate and accessible records. Using validated data management systems and staying up-to-date with industry best practices can help address these challenges and ensure high-quality, reliable data.

What is the difference between Biotech Data Management vs Biotech Data Analyst?

AspectBiotech Data ManagementBiotech Data Analyst
Required CredentialsBachelor's in Life Sciences, Bioinformatics, or related; familiarity with database systemsBachelor's in Biology, Statistics, or related; proficiency in data analysis tools
Work EnvironmentData management teams, laboratories, biotech companiesResearch teams, biotech firms, data analysis departments
Employer & Industry UsageUsed across biotech, pharmaceutical, and research organizations for data organizationUsed for interpreting data, generating reports, and supporting research decisions

Biotech Data Management focuses on organizing, maintaining, and ensuring data integrity within biotech organizations, often involving database systems and data quality control. In contrast, Biotech Data Analysts interpret and analyze data to generate insights, reports, and support research outcomes. While both roles require strong data skills, Data Management emphasizes data storage and quality, whereas Data Analysis emphasizes data interpretation and reporting.

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Biotech Data Management jobs near you
Infographic showing various Biotech Data Management job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 14% Part Time, and 2% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $68,795 per year, or $33.1 per hour.

BioTech Data Engineer

Stellar IT Group

Saint Louis, MO • On-site

$111K - $133K/yr

Full-time

Re-posted yesterday

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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