Python Engineer

About
Propel

At Propel, we don't just
build software — we build future -ready, human -centered digital platforms that
drive business transformation. We are a design -led technology firm committed to
solving complex problems with elegant, scalable solutions. Join a workplace
where your ideas matter, your expertise is valued, and your growth is championed.

About
the Role

As a Python Data Engineer on
our team, you will be responsible for designing, building, and maintaining
scalable data pipelines, data processing systems, and backend services. You
will work closely with engineering, analytics, and product teams to deliver
reliable, high -quality data solutions that support reporting, automation, and
decision -making.

Key
Responsibilities

• Design, develop, and maintain robust data
  pipelines using Python.
  
• Build and maintain backend services and
  background jobs using modern Python frameworks such as FastAPI.
  
• Perform data processing, transformation, and
  reporting using libraries like Pandas, Polars, DuckDB, and openpyxl.
  
• Design and implement scalable data architectures
  including data lakes, medallion architecture, and star schemas.
  
• Develop, test, and deploy data workflows using
  orchestration tools such as Airflow.
  
• Collaborate with teams to implement CI/CD
  pipelines using GitHub Actions.
  
• Develop and deploy solutions on Microsoft Azure
  using services such as Container Apps, Azure Storage, Service Bus, and
  SignalR.
  
• Implement Infrastructure as Code (IaC) using
  Bicep; collaborate with teams using Terraform or AWS CDK where applicable.
  
• Follow spec -driven development practices and
  leverage AI -assisted development tools.
  
• Write clean, maintainable, and well -documented
  code following best practices.
  
• Participate in code reviews, testing, and
  production support activities.
  
• Collaborate with cross -functional teams to ensure
  consistency and reliability of data solutions.
  

What
We’re Looking For

·       Bachelor’s degree in computer science, engineering, or a related field.

·       Strong Python Experience (web services, background jobs; we use FastAPI)

·       Data processing and reporting using Python (Pandas, Polars, openpyxl and
DuckDB are used; Airflow, dbt, streamlit experience is nice to have)

·       Experience with data pipeline design (data lake, medallion architecture,
star schema) Experience with CI/CD (GitHub Actions is used) Azure development
experience (Container Apps, Azure Storage, Service Bus, SignalR)

·       Experience with IaC automation (Bicep@Azure is used; AWS CDK, Terraform
experience is transferrable)

·       Spec -Driven Development with AI (GitHub Copilot and Claude Code are used)

Preferred

• Distributed Processing, async workflows, enterprise messaging
  patterns Snowflake (stored procedures, streams, tasks, pipes, time travel).
  
• Experience with .NET web development (part of the legacy frontend is
  implemented in .NET Core)
  
• Web development and angular or nextjs
  

What
We Offer

A
Purpose -Driven Mission

We believe in using
technology as a force for good—designing scalable, data -driven systems that
enable smarter decisions and meaningful impact across industries.

Empowered
& Inclusive Culture

Our open and collaborative
culture ensures your ideas matter. You’ll have the autonomy to design solutions
while working closely with highly skilled teams.

Learning
& Growth at the Core

From mentorship and
certifications to hands -on exposure to modern data platforms, we invest deeply
in your professional growth.

Innovation
with Impact

You’ll work on modern data
platforms and cloud -native architectures, helping clients unlock insights
through automation, analytics, and intelligent systems.

Well -being
Matters

We prioritize work -life
harmony, psychological safety, and policies that support your mental, physical,
and professional well -being.

Others:

·       Common application/ web security and OWASP vulnerabilities

·       Encryption algorithms to protect sensitive information

·       PII, PCI, HIPPA, and GDPR compliance and how to implement

·       Finding the vulnerabilities of the third -party components/ libraries

·       Understanding security breaches of data -in -transit and data -at -rest and
its implementation