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Junior Python Analyst Jobs in Troy, MI (NOW HIRING)

Hart

Junior Data Analyst

Detroit, MI · On-site

SUMMARY We're looking for a proactive and insightful Junior Data Analyst to join our Analytics team ... Some exposure to basic coding/scripting (SQL, Python) is a plus * Basic understanding of ETL ...

Hart

Junior Data Analyst

Detroit, MI · On-site

SUMMARY We're looking for a proactive and insightful Junior Data Analyst to join our Analytics team ... Python) is a plus • Basic understanding of ETL processes and how data is collected, merged ...

Hart, Inc.

Junior Data Analyst

Detroit, MI · On-site

SUMMARY We're looking for a proactive and insightful Junior Data Analyst to join our Analytics team ... Some exposure to basic coding/scripting (SQL, Python) is a plus * Basic understanding of ETL ...

Socket.dev

Junior AI/ML Engineer

Auburn Hills, MI · On-site

Run and document model validation, evaluation, and error analysis under senior guidance * Build ... Write clean, maintainable, and testable code (primarily Python), responding constructively to code ...

Technomics, Inc.

Data Analyst

Troy, MI · On-site

... mix of junior and mid-level analysts. Our employee-owners pride themselves on their ability to ... Relevant experience includes Python, SQL, JavaScript/TypeScript, ETL/ELT, low-code development ...

Technomics

Data Analyst

Troy, MI

... mix of junior and mid-level analysts. Our employee-owners pride themselves on their ability to ... Relevant experience includes Python, SQL, JavaScript/TypeScript, ETL/ELT, low-code development ...

Huntington

Threat Detection Analyst (Expert)

Detroit, MI · On-site

$70K - $140K/yr

Provide leadership, mentorship, and training opportunities for junior Threat Detection Analysts ... Experience with scripting and automation using Python, PowerShell, Bash, or similar languages.

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Junior Python Analyst information

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How much do junior python analyst jobs pay per hour?

As of Sep 12, 2026, the average hourly pay for junior python analyst in Troy, MI is $30.44, according to ZipRecruiter salary data. Most workers in this role earn between $21.88 and $33.51 per hour, depending on experience, location, and employer.

What is the difference between Junior Python Analyst vs Junior Data Analyst?

AspectJunior Python AnalystJunior Data Analyst
Required SkillsPython programming, data analysis, basic SQLExcel, SQL, data visualization tools
CertificationsPython certifications, data analysis coursesExcel, Tableau, SQL certifications
Work EnvironmentTech companies, data-driven teamsBusiness, marketing, finance sectors
Common TasksWriting Python scripts, data cleaning, automationData reporting, dashboard creation, data interpretation

While both roles involve data analysis, Junior Python Analysts focus on coding with Python and automating data processes, whereas Junior Data Analysts primarily work with Excel and visualization tools to interpret data. The choice depends on your technical skills and career interests in programming versus traditional data analysis.

Junior Python Analyst jobs near you

Python Technical Architect/ Lead

Auburn Hills, MI • On-site

Conflux Systems
IT Services • 11 - 50 employees
Learn more about Conflux Systemsexternal

$138K - $169K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Job Title: Sr Python Developer & Lead
Location: Auburn Hills, MI- Onsite
Remote work: No
Mandatory Skills: Data Engineering, Python, PySpark, CI/CD, Airflow, Workflow Orchestration
Key Responsibilities
1. Data Engineering: Design, develop, and optimize scalable data pipelines using Python and PySpark for batch and streaming workloads.
2. Workflow Orchestration: Build, schedule, and monitor complex workflows using Airflow, ensuring reliability and maintainability.
3. CI/CD Pipeline Development: Architect and implement CI/CD pipelines for data engineering projects using GitHub, Docker, and cloud-native solutions.
4. Testing & Quality: Apply test-driven development (TDD) practices and automate unit/integration tests for data pipelines.
5. Secure Development: Implement secure coding best practices and design patterns throughout the development lifecycle.
6. Collaboration: Work closely with Data Architects, QA teams, and business stakeholders to translate requirements into technical solutions.
7. Documentation: Create and maintain technical documentation, including process/data flow diagrams and system design artifacts.
8. Mentorship: Lead and mentor junior engineers, providing guidance on coding, testing, and deployment best practices.
9. Troubleshooting: Analyze and resolve technical issues across the data stack, including pipeline failures and performance bottlenecks.
Technical Experience:
1. Hands-on Data Engineering : Minimum 5+ yearsof practical experience building production-grade data pipelines using Python and PySpark.
2. Airflow Expertise: Proven track record of designing, deploying, and managing Airflow DAGs in enterprise environments.
3. CI/CD for Data Projects : Ability to build and maintain CI/CD pipelinesfor data engineering workflows, including automated testing and deployment**.
4. Cloud & Containers: Experience with containerization (Docker and cloud platforms (GCP) for data engineering workloads. Appreciation for twelve-factor design principles
5. Python Fluency : Ability to write object-oriented Python code manage dependencies, and follow industry best practices
6. Version Control: Proficiency with **Git** for source code management and collaboration (commits, branching, merging, GitHub/GitLab workflows).
7. Unix/Linux: Strong command-line skills** in Unix-like environments.
8. SQL : Solid understanding of SQL for data ingestion and analysis.
9. Collaborative Development : Comfortable with code reviews, pair programming and usingremote collaboration tools effectively.
10. Engineering Mindset: Writes code with an eye for maintainability and testability; excited to build production-grade software
11. Education: Bachelor's or graduate degree in Computer Science, Data Analytics or related field, or equivalent work experience.
• A high tolerance for OpenShift, Cloudera, Tableau, Confluence, Jira, and other enterprise tools.

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