Associate Director, Principal Data Engineer

Scorpion Therapeutics; San Francisco (CA); On-site; USD 180,000 - 260,000; Full time

Job summary

Scorpion Therapeutics, based in San Francisco, seeks an Associate Director, Principal Data Engineer to lead the design and delivery of AI-enabled research platforms and scalable data pipelines. You will shape trusted LLM-driven workflows, governance, and cross-functional collaboration to accelerate bioinformatics and genomic insights.

The role requires senior technical leadership, deep cloud expertise, and hands-on skills in Python/Java with experience across Databricks, AWS, and data pipelines.

Qualifications

• 12+ years in data engineering, software engineering, scientific computing, cloud architecture, or scientific application.
• Strong hands-on Python and/or Java; scalable data pipelines, APIs/services, production-grade data.
• Experience with AI/ML-enabled scientific applications using LLMs (GPT, Claude, Gemini, etc.); RAG, knowledge search, agentic workflows, governance.
• Strong AWS experience (compute/storage/networking/security/data processing/monitoring/automation/operations).
• Experience integrating LIMS/ELN/scientific data platforms or Experimenta for capture, analysis, and quality review.
• Demonstrated technical leadership and cross-functional communication.

Responsibilities

• Build AI-enabled research workflows and agents to help scientists search, analyze, summarize, and connect Vir-generated information.
• Develop AI agents for TCE research insights, Experimenta QC/QA review, and scientific/regulatory reporting.
• Design trusted LLM, RAG, knowledge-search, and agentic AI workflows with traceability, validation, governance, and human oversight.
• Lead development and integration of scientific platforms (e.g., SeqAssembler, HPD/dAIsY, SASTRY, OPAL Miner).
• Build scalable research and clinical data pipelines for bioinformatics, genomics, machine learning, and scientific decision-making.
• Architect and operate AWS cloud infrastructure for AI/ML, bioinformatics, clinical analysis, and large-scale scientific data.
• Strengthen data quality, metadata, lineage, observability, security, and governance.
• Partner cross-functionally to align data, cloud, application, and AI solutions with program needs.
• Provide senior technical leadership (architecture, engineering practices, mentoring, roadmap).

Skills

Python

Java

Data pipelines

APIs / Services

LLMs / AI apps

AWS

Databricks

Snowflake

Spark

Airflow

Nextflow

Leadership

Cross-functional communication

Bioinformatics / Genomics knowledge

Data governance

Education

BS/MS in Computer Science, Data Engineering, Bioinformatics, Computational Biology, Engineering, or related technical field

Tools

AWS

Databricks

Snowflake

Spark

Airflow

Nextflow

Job description

Associate Director, Principal Data Engineer

Responsibilities:

• Build AI-enabled research workflows and agents to help scientists search, analyze, summarize, and connect Vir-generated information.
• Develop AI agents for TCE research insights, Experimenta QC/QA review, and scientific/regulatory reporting.
• Design trusted LLM, RAG, knowledge-search, and agentic AI workflows with traceability, validation, governance, and human oversight.
• Lead development and integration of scientific platforms (e.g., SeqAssembler, HPD/dAIsY, SASTRY, OPAL Miner).
• Build scalable research and clinical data pipelines for bioinformatics, genomics, machine learning, and scientific decision-making.
• Architect and operate AWS cloud infrastructure for AI/ML, bioinformatics, clinical analysis, and large-scale scientific data.
• Strengthen data quality, metadata, lineage, observability, security, and governance.
• Partner cross-functionally to align data, cloud, application, and AI solutions with program needs.
• Provide senior technical leadership (architecture, engineering practices, mentoring, roadmap).

Qualifications:

• BS/MS in Computer Science, Data Engineering, Bioinformatics, Computational Biology, Engineering, or related technical field.
• 12+ years in data engineering, software engineering, scientific computing, cloud architecture, or scientific application.
• Strong hands‑on Python and/or Java; scalable data pipelines, APIs/services, production‑grade data.
• Experience with AI/ML-enabled scientific applications using LLMs (GPT, Claude, Gemini, etc.); RAG, knowledge search, agentic workflows, governance.
• Experience integrating LIMS/ELN/scientific data platforms or Experimenta for capture, analysis, and quality review.
• Strong AWS experience (compute/storage/networking/security/data processing/monitoring/automation/operations).
• Experience with Databricks, Snowflake, Redshift, Spark, Airflow, Nextflow, or similar.
• Experience supporting bioinformatics/genomics/ML/clinical or other scientific data.
• Knowledge of data modeling, metadata management, data quality, observability, governance, lineage.
• Demonstrated technical leadership and cross‑functional communication.