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Clinical Research Data Engineer Jobs (NOW HIRING)

Alphatec Spine

Research Data Engineer

Carlsbad, CA

$118K - $142K/yr

We are a US-based company focused on advancing clinical research and medical technologies. We are seeking a Research Data Engineer to support clinical research activities by building and maintaining ...

Alphatec Spine

Research Data Engineer

Carlsbad, CA

$110K - $130K/yr

We are a US-based company focused on advancing clinical research and medical technologies. We are seeking a Research Data Engineer to support clinical research activities by building and maintaining ...

Alphatec Spine

Research Data Engineer

Carlsbad, CA · On-site

$110K - $130K/yr

We are a US-based company focused on advancing clinical research and medical technologies. We are seeking a Research Data Engineer to support clinical research activities by building and maintaining ...

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Clinical Research Data Engineer information

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$37K

$106K

$142.5K

How much do clinical research data engineer jobs pay per year?

As of Jun 8, 2026, the average yearly pay for clinical research data engineer in the United States is $106,012.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,000.00 and $104,000.00 per year, depending on experience, location, and employer.

What is the difference between Clinical Research Data Engineer vs Clinical Data Analyst?

AspectClinical Research Data EngineerClinical Data Analyst
Required CredentialsBachelor's or higher in computer science, bioinformatics, or related field; knowledge of data engineering toolsBachelor's or higher in life sciences, statistics, or related field; proficiency in data analysis software
Work EnvironmentData infrastructure development, database management, coding in SQL, Python, or RData interpretation, reporting, statistical analysis, visualization
Employer & Industry UsagePharmaceutical companies, CROs, biotech firms focusing on data pipeline setupClinical research organizations, hospitals, biotech firms analyzing trial data

The Clinical Research Data Engineer primarily focuses on building and maintaining data infrastructure for clinical trials, while the Clinical Data Analyst interprets and reports on the data collected. Both roles require strong data skills but differ in technical focus and daily tasks.

Research Data Engineer

Research Data Engineer

Alphatec Spine

Carlsbad, CA

$118K - $142K/yr

Full-time

Posted 18 days ago

Job description

We are a US-based company focused on advancing clinical research and medical technologies. We are seeking a Research Data Engineer to support clinical research activities by building and maintaining reliable data pipelines and preparing high-quality datasets for researchers and analysts. This role emphasizes batch data processing, data quality, data transformation and processing and enabling efficient, compliant access to research data.

Essential Duties and Responsibilities

Clinical Research Data Support:

  • Ingest, process, and manage clinical and research datasets from internal and external sources.
  • Design data models and datasets optimized for researcher and analyst use.
  • Maintain datasets used in research studies, ensuring consistency, traceability, and documentation.

Batch Data Engineering:

  • Design, build, and maintain batch data pipelines for scheduled ingestion, transformation, and delivery.
  • Optimize and monitor batch workflows to ensure performance, reliability, and scalability.
  • Troubleshoot and resolve issues in data pipelines and scheduled jobs.

Data Quality and Governance:

  • Implement data validation, quality checks, and monitoring processes.
  • Identify and resolve data inconsistencies, anomalies, and gaps.
  • Ensure compliance with healthcare data regulations (e.g., HIPAA, GDPR).

Analytics Enablement:

  • Partner with researchers and analysts to deliver clean, well-structured datasets.
  • Develop SQL queries and data transformations to support reporting and analysis.
  • Assist with exploratory data analysis and data preparation workflows.

Collaboration and Documentation:

  • Work cross-functionally with clinical, analytics, and engineering teams.
  • Document data pipelines, schemas, and workflows to ensure transparency and reproducibility.

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