Senior Python Data Engineer - Remote, AWS & Data Pipelines

Socket.dev; United States; On-site; USD 120,000 - 180,000; Full time

Job summary

3Pillar Global is seeking a Senior Data Python + AWS Engineer who will build robust data pipelines, models, and dashboards for enterprise clients. You will work across data acquisition, processing, and visualization, delivering insights with Streamlit, Tableau, and Jupyter to empower decision-making.

This remote-first role requires strong communication, 5+ years in data engineering, and the ability to translate complex data problems into scalable solutions while collaborating with product and

Qualifications

• 5+ years as a Data Engineer or similar role.
• 3+ years of Python and SQL experience focusing on data.
• Experience with data plotting/dashboarding tools (Streamlit/Tableau/Jupyter) is a plus.
• Excellent communication and ability to drive project delivery.
• Ability to understand a highly technical product and communicate with product/engineering teams.

Responsibilities

• Develop and refine data acquisition strategies from scientific instruments.
• Build and operationalize parsers for diverse outputs (.xlsx, .pdf, .txt, .raw, .fid, etc.).
• Architect scalable data models and pipelines with tests and reusable libraries.
• Compare datasets to design shared data model components.
• Create visualizations and dashboards using Streamlit, Tableau, and Jupyter.

Skills

Python

SQL

Data modeling

Data pipelines

Visualization

Communication

Education

Bachelor's degree in biology/chemistry or related field

Tools

Streamlit

Tableau

Jupyter Notebook

AWS

Job description

3Pillar Global is seeking a Senior Data Python + AWS Engineer who will build robust data pipelines, models, and dashboards for enterprise clients. You will work across data acquisition, processing, and visualization, delivering insights with Streamlit, Tableau, and Jupyter to empower decision-making.

This remote-first role requires strong communication, 5+ years in data engineering, and the ability to translate complex data problems into scalable solutions while collaborating with product and