AWS Data Engineer – Pharma / Life Sciences

Hybrid in San Francisco, CA, US • Posted 13 hours ago • Updated 13 hours ago
Contract W2
Contract Independent
12 Months
No Travel Required
Hybrid
Depends on Experience
Fitment

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Job Details

Skills

  • AWS Data Engineer
  • Pharma
  • Life Sciences
  • AWS

Summary

Job Title: AWS Data Engineer – Pharma / Life Sciences

 

Location: San Francisco, California(Hybrid)

Contract

 

Job Summary

 

We are seeking a highly skilled AWS Data Engineer with strong experience in the Pharmaceutical / Life Sciences domain to design, build, and maintain scalable data pipelines and platforms. The ideal candidate will have deep expertise in AWS data services, big data technologies, and a strong understanding of clinical, regulatory, and pharmaceutical data processes.

 

You will play a critical role in enabling data-driven decision-making across drug development, clinical trials, and commercial operations while ensuring compliance with industry regulations.

 

Key Responsibilities

Design, develop, and optimize scalable ETL/ELT pipelines using AWS services.

Build and maintain data lakes and data warehouses on AWS (S3, Redshift, Glue, EMR).

Develop robust data ingestion frameworks for structured and unstructured data sources.

Work with large-scale datasets including clinical, research, and real-world evidence (RWE) data.

Implement data transformation and processing using PySpark, Spark, and SQL.

Ensure data quality, integrity, and compliance with pharma regulations (GxP, FDA, 21 CFR Part 11).

Collaborate with data scientists, analysts, and business stakeholders to deliver data solutions.

Optimize performance, scalability, and cost-efficiency of AWS data platforms.

Implement monitoring, logging, and alerting using AWS CloudWatch and related tools.

Maintain documentation for data pipelines, architecture, and data models.

Required Skills & Experience

Technical Skills

Strong experience with AWS services: Glue, S3, Redshift, EMR, Athena, Lambda, Kinesis

Proficiency in Python, PySpark, and SQL

Hands-on experience with big data technologies (Spark, Hadoop, Databricks)

Experience building ETL/ELT pipelines and data lakes

Knowledge of data modeling, data warehousing, and data architecture principles

Familiarity with workflow orchestration tools (Airflow, Step Functions)

Domain Experience

Strong experience in Pharmaceutical / Life Sciences industry

Understanding of clinical trials, drug development, and regulatory data

Experience working with healthcare/pharma datasets (RWD, RWE, EHR, claims data)

ompliance & Governance

Knowledge of GxP, GMP, FDA regulations, 21 CFR Part 11

Experience implementing data governance, security, and compliance frameworks

Preferred Qualifications

Experience with Databricks or Snowflake

Exposure to CI/CD pipelines and DevOps practices

AWS Certifications (e.g., AWS Certified Data Engineer / Solutions Architect)

Experience with data cataloging and governance tools

 

Education

Bachelor’s or Master’s degree in Computer Science, Data Engineering, Life Sciences, or related field

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 91093425
  • Position Id: 8990428
  • Posted 13 hours ago
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Dhruba Bhusal

Dhruba Bhusal

Recruiter @ TUPPL Technology Inc
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