

AI Data Engineer
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Part-Time AI Data Engineer in the San Francisco Bay Area, offering a 20-hour/week contract at an unspecified pay rate. Requires 3-5 years of experience, proficiency in Python, and knowledge of AI/ML data pipelines.
π - Country
United States
π± - Currency
$ USD
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π° - Day rate
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ποΈ - Date discovered
July 26, 2025
π - Project duration
More than 6 months
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ποΈ - Location type
On-site
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π - Contract type
Unknown
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π - Security clearance
Unknown
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π - Location detailed
South San Francisco, CA
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π§ - Skills detailed
#Data Engineering #Data Pipeline #Metadata #API (Application Programming Interface) #Data Management #Data Science #ML (Machine Learning) #Docker #Datasets #"ETL (Extract #Transform #Load)" #Python #Scala #Monitoring #Data Profiling #AWS (Amazon Web Services) #AI (Artificial Intelligence) #Data Governance #Strategy
Role description
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Dice is the leading career destination for tech experts at every stage of their careers. Our client, Advanced Software Talent, is seeking the following. Apply via Dice today!
Part-Time or Full-time Data Engineer (San Francisco Bay Area Only)
Local Candidates Only | No Third-Party Agencies | No Visa Sponsorship Available
We are seeking a Part-Time Data Engineer to join a cutting-edge team focused on AI innovation in the pharmaceutical industry. This is a 20-hour-per-week contract position. Candidates can choose to work either 4 hours per day across 5 days or 5 hours per day across 4 days.
Please Note:
β’ Only candidates currently residing in the San Francisco Bay Area will be considered.
β’ We are not working with third-party agencies.
β’ Visa sponsorship is not available for this role.
β’ Candidates with more than 5 years of professional experience will not be considered.
About the Team: AI Emerging Tech & External Collaborations
You ll be joining a strategic innovation team driving the adoption of AI-enabled solutions and next-generation technologies to support our Pharma and DIA Partnering functions. Our focus is on building scalable data infrastructure, integrating external research capabilities, and enabling end-to-end AI workflows to accelerate decision-making and unlock real business value.
From collaborating with external research partners to shaping internal AI strategy, this is a unique opportunity to help define how data and AI transform a global organization.
Role Overview
As a Data Engineer, you will play a key role in architecting, building, and maintaining robust data systems that support machine learning and advanced analytics. You ll collaborate closely with data scientists, business stakeholders, and external collaborators to develop clean, accessible, and well-modeled datasets essential for AI innovation.
Key Responsibilities
β’ Design & Build Scalable Data Pipelines: Develop and maintain pipelines for ingesting, transforming, and curating structured and unstructured data.
β’ Data Profiling & Standardization: Analyze and align data sources, identify quality issues, and define models to support AI/ML use cases.
β’ Data Product & API Development: Build reusable, secure data assets and APIs for analytics and machine learning workloads.
β’ Infrastructure Architecture: Help design and implement scalable data platforms, including AWS-based data hubs.
β’ AI/ML Integration: Ensure data solutions support downstream AI applications, including LLMs and AI agents.
β’ Metadata & Governance: Embed data governance, lineage, and metadata practices into all solutions.
β’ Monitoring Frameworks: Develop real-time data monitoring and alert systems.
β’ Workflow Orchestration: Manage containerized workloads (e.g., Docker) and use orchestration tools like Amazon EKS or Google Agent Development Kit (ADK).
β’ Continuous Improvement: Evaluate and refine data tools, processes, and platforms for performance and scalability.
Required Qualifications
β’ Bachelor s or Master s degree in Computer Engineering, Data Science, or a related field
β’ 3 5 years of professional experience as a Data Engineer in an enterprise environment
β’ Strong proficiency in Python
β’ Experience with AI/ML data pipelines
β’ Knowledge of data governance and metadata management best practices
β’ Excellent written and verbal communication skills