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Python Data Jobs (NOW HIRING)

TriosysIT Inc.

Python Developer

Columbus, OH · On-site

$47 - $64.75/hr

Python data processing technologies, e.g. Pandas, Numpy * Solid understanding on web applications, e.g. HTML, CSS, javascript * Solid understanding on DB and SQL

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How much do python data jobs pay per hour?

As of Jul 27, 2026, the average hourly pay for python data in the United States is $58.62, according to ZipRecruiter salary data. Most workers in this role earn between $48.32 and $66.59 per hour, depending on experience, location, and employer.

What is the salary for Python data analytics?

The salary for Python data analysts typically ranges from $60,000 to $100,000 annually, depending on experience, location, and industry. Professionals with strong skills in data manipulation, visualization, and tools like Pandas and SQL tend to earn higher salaries.

What Python jobs are in demand?

Python data-related jobs in demand include data analyst, data scientist, machine learning engineer, and backend developer. These roles often require proficiency in libraries like Pandas, NumPy, and frameworks such as TensorFlow, with employers seeking strong programming skills and experience with data analysis or AI projects.

What are some common challenges faced by Python Data professionals when working with large datasets?

Python Data professionals often encounter challenges such as optimizing code to handle large volumes of data efficiently and managing memory usage to prevent slowdowns or crashes. Working with big datasets may require leveraging tools like pandas, NumPy, or Dask, and sometimes integrating with distributed computing systems such as Apache Spark. Additionally, ensuring data quality and managing data pipelines for consistent and accurate results can be demanding. Collaborating closely with data engineers, analysts, and other stakeholders is common to ensure smooth data flow and analysis.

What is a Python Data professional?

A Python Data professional is someone who uses the Python programming language to analyze, process, and interpret data. They work with large datasets, perform data cleaning and transformation, and apply statistical or machine learning techniques to extract insights. These professionals often work in roles such as data analyst, data scientist, or data engineer, and use Python libraries like Pandas, NumPy, and scikit-learn to accomplish their tasks.

Will AI replace Python devs?

Python developers are unlikely to be fully replaced by AI, as their role involves designing, coding, and maintaining complex software systems that require human judgment and creativity. AI tools can assist with tasks like code generation and debugging, but human oversight remains essential for quality and innovation. Staying updated with new frameworks and machine learning techniques can help Python developers remain valuable in the evolving tech landscape.

What is the difference between Python Data vs Data Analyst?

AspectPython DataData Analyst
Required SkillsPython programming, data manipulation, scriptingExcel, SQL, data visualization
CertificationsPython certifications, data science coursesData analysis certifications, Excel certifications
Work EnvironmentData science teams, programming-heavy rolesBusiness intelligence, reporting teams
Industry UsageTech, finance, healthcareRetail, marketing, finance

Python Data roles focus on programming, data manipulation, and building data pipelines using Python, while Data Analysts primarily analyze data using tools like Excel and SQL to generate reports and insights. Both roles often collaborate but differ in technical depth and tools used.

What type of jobs can I get with Python?

Python is used in a variety of roles including software developer, data analyst, data scientist, machine learning engineer, and automation engineer. These jobs often require knowledge of libraries like Pandas, NumPy, and frameworks such as TensorFlow or Django, and may involve working in environments like cloud platforms or data centers.

What are the key skills and qualifications needed to thrive as a Python Data professional, and why are they important?

To thrive as a Python Data professional, you need strong programming skills in Python, a solid understanding of data structures, algorithms, and experience with data analysis or data science, typically supported by a relevant degree. Familiarity with technical tools such as pandas, NumPy, SQL, Jupyter Notebooks, and often cloud platforms or machine learning frameworks is important, and certifications like Microsoft or Google Data certifications can be advantageous. Strong analytical thinking, attention to detail, and effective communication help you extract insights from data and collaborate with stakeholders. These skills and qualities are essential to efficiently process, analyze, and interpret data, driving informed business decisions.
More about Python Data jobs
What cities are hiring for Python Data jobs? Cities with the most Python Data job openings:
What states have the most Python Data jobs? States with the most job openings for Python Data jobs include:
What job categories do people searching Python Data jobs look for? The top searched job categories for Python Data jobs are:
Python Data jobs near you
Infographic showing various Python Data job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $121,932 per year, or $58.6 per hour.
Technology Lead Python Data Engineer

Technology Lead Python Data Engineer

Citigroup, Inc.

Rutherford, NJ • On-site

$142K - $175K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 10 days ago

Job description

Discover Your Future in Credit Risk Technology
Build systems that shape credit decisions-at scale.
Join a fast-moving Credit Risk Technology team where modern engineering, data, and AI come together to drive real-world financial impact. We operate with a startup mindset-ownership, speed, and experimentation-within the rigor and responsibility of a global financial institution. You'll help design and deliver mission-critical platforms that support credit risk assessment, analytics, and decisioning across the firm.
Job Overview
The Technology Lead Python Data Engineeris a senior engineering leadership role focused on building and evolving modern, scalable platforms for credit risk management. You will lead application design and development while partnering closely with risk, data, and platform teams to deliver systems that are performant, resilient, and compliant.
This role blends hands-on development, system architecture, technical leadership, and AI-enabled innovation, with a strong emphasis on microservices, cloud-native design, and enterprise-grade governance.
Key Responsibilities
  • Architect, design, and deliver scalable, Python-based applications supporting credit risk analytics, workflows, and reporting.
  • Partner with risk, product, and technology leadership to integrate platforms, identify enhancements, and enable new products and process improvements.
  • Resolve high-impact, complex initiatives through deep analysis of business processes, system flows, and industry standards.
  • Ensure solutions adhere to enterprise architecture, data, security, and infrastructure blueprints.
  • Establish and enforce engineering standards for coding, testing, CI/CD, debugging, and production readiness.
  • Design and evolve microservices-based architectures, ensuring scalability, resiliency, observability, and maintainability.
  • Apply AI and GenAI capabilities to modernize workflows, automate analysis, and unlock new insights in credit risk.
  • Serve as technical leader and mentor, coaching mid-level engineers and analysts and allocating work as needed.
  • Apply sound risk and control judgment, ensuring compliance with laws, regulations, and policies while safeguarding clients, data, and the firm.

How You'll Work
  • Operate with a startup mindset: ownership, bias for action, and pragmatic innovation.
  • Deliver with enterprise discipline: stability, controls, transparency, and audit readiness.
  • Balance experimentation with responsibility in a high-trust, high-impact environment.
  • Adapt quickly as priorities change while maintaining long-term system integrity.

Core Technical Skills
  • 10-15 years of experience in application development or systems engineering within complex environments.
  • Advanced proficiency in Python and SQL, with strong software engineering fundamentals.
  • Hands-on experience building API-driven services using FastAPI, Pydantic, and/or Django.
  • Proven expertise designing and implementing microservices architectures, including service decomposition, inter-service communication, resiliency patterns, and observability.
  • Strong experience with Docker and Kubernetes, deploying and operating containerized services in production.
  • Deep understanding of system architecture, data flows, and distributed systems.
  • Experience working in Linux environments, including shell scripting and operational troubleshooting.
  • Strong track record implementing unit testing, TDD, and automated quality controls.
  • Subject Matter Expert (SME) in at least one application, platform, or service domain.

AI & Modern Engineering Tools
  • Working knowledge of large language models (LLMs) and modern AI platforms from leading providers such as OpenAI, Anthropic, Google, and Meta.
  • Experience designing or contributing to LLM-enabled solutions (e.g., copilots, workflow automation, analytics augmentation).
  • Familiarity with prompt engineering, model integration patterns, and AI governance considerations in enterprise environments.
  • Exposure to modern "vibe coding" practices-leveraging AI-assisted tooling to accelerate development, experimentation, and problem solving while maintaining engineering rigor.

Bonus / Differentiating Skills
  • Experience with distributed data and compute platforms (e.g., Spark, PySpark, Hadoop, Hive).
  • Hands-on experience with graph databases, particularly Neo4j, for network, relationship, or dependency-driven use cases.
  • Background in credit risk, financial risk management, or banking platforms.
  • Experience modernizing or decomposing legacy monolithic systems in large enterprises.
  • Proven delivery of GenAI / AI-driven solutions in regulated or large-scale environments.

Education
  • Bachelor's degree (or equivalent experience) in Computer Science, Engineering, Mathematics, or a related STEM field.
  • Master's degree preferred.

Job Family Group:
Technology
Job Family:
Applications Development
Time Type:
Full time
Primary Location:
Rutherford New Jersey United States
Primary Location Full Time Salary Range:
$142,320.00 - $213,480.00
In addition to salary, Citi's offerings may also include, for eligible employees, discretionary and formulaic incentive and retention awards. Citi offers competitive employee benefits, including: medical, dental & vision coverage; 401(k); life, accident, and disability insurance; and wellness programs. Citi also offers paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays. For additional information regarding Citi employee benefits, please visit citibenefits.com. Available offerings may vary by jurisdiction, job level, and date of hire.
Most Relevant Skills
Please see the requirements listed above.
Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter.
Anticipated Posting Close Date:
May 28, 2026
Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.
If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi.
View Citi's EEO Policy Statement and the Know Your Rights poster.

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