Senior Python Engineer — Data Pipelines & Time-Series (Hybrid)

Medix™; Santa Clarita (CA); Hybrid; USD 150,000 - 190,000; Full time

Job summary

Medix is seeking a Senior Python Software Engineer with deep hands-on Python, Pandas, NumPy, and a foundation in quantitative methods to build production-grade data pipelines and work with a research team on real-world engineering problems.

This role involves time-series data processing, ETL workflows, EDA, and translating algorithms into robust, well-tested Python software in collaboration with software and embedded teams.

Qualifications

• 5+ years of professional software engineering experience.
• Strong Python proficiency.
• Extensive hands-on Pandas and NumPy experience.
• Experience building production-grade Python data pipelines.
• Understanding of OO design, code reviews, documentation, debugging and performance tuning.
• Experience with structured, numerical, or time-series data.
• BS/MS in CS/EE/Applied Mathematics or related quantitative field.

Responsibilities

• Build, test, and maintain production-quality Python applications and data pipelines.
• Work with Pandas and NumPy for data manipulation and feature engineering.
• Develop efficient ETL workflows for large datasets.
• Perform exploratory data analysis and statistical analysis.
• Process and analyze time-series and experimental data.
• Translate algorithms into production implementations with other engineers.
• Write clean, modular Python code with unit tests and documentation.
• Profile and optimize Python workflows for performance and scalability.
• Collaborate with software and embedded teams to integrate algorithms.

Skills

Python

Pandas

NumPy

Data pipelines

Time-series

EDA

Quantitative methods

Software engineering

Education

B.S./M.S. in CS/EE/Applied Math

Tools

SciPy

Matplotlib

Plotly

scikit-learn

Job description

Medix is seeking a Senior Python Software Engineer with deep hands-on Python, Pandas, NumPy, and a foundation in quantitative methods to build production-grade data pipelines and work with a research team on real-world engineering problems.

This role involves time-series data processing, ETL workflows, EDA, and translating algorithms into robust, well-tested Python software in collaboration with software and embedded teams.