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Python Data Analyst Jobs in North Carolina (NOW HIRING)

Data Analyst Location: Charlotte, NC Mode Of Work: Hybrid It's a W2 role * Develop analytics ... Write python scripts to develop ETL jobs Required Skills (top 3 non-negotiables): * Looker and ...

Data Analyst Location: Charlotte, NC Mode Of Work: Hybrid It's a W2 role * Develop analytics ... Write python scripts to develop ETL jobs Required Skills (top 3 non-negotiables): * Looker and ...

Ability to use Python to automate and organize ETL processes. Perform ad hoc reports and provide ... skills in data analysis and reporting Proficiency level in Excel Fluent in English and ...

Experience with Python or R for data analysis and automation. * Exposure to cloud platforms such as AWS, Azure, or Google Cloud. * Knowledge of ETL processes and data integration tools. * Experience ...

Familiarity with Python (Pandas, NumPy) or R for statistical analysis. * Understanding of data modeling concepts and collaboration with Data Engineers. * Excellent communication and presentation ...

Sr. Data Analyst

Charlotte, NC ยท On-site

$84K - $106K/yr

The ideal candidate will have deep expertise in SQL and Python , the ability to independently analyze complex datasets, identify data issues, and support business and technology teams in an Agile ...

$81K - $95K/yr

Analyze large, relational datasets to identify trends, inefficiencies, and performance gaps ... Develop scripts using Python, Bash, or PowerShell * Automate data pulls, file processing, and ...

Data Analyst

Cherry Point, NC ยท On-site

$81K - $95K/yr

Analyze large, relational datasets to identify trends, inefficiencies, and performance gaps ... Develop scripts using Python, Bash, or PowerShell * Automate data pulls, file processing, and ...

Analyze large, relational datasets to identify trends, inefficiencies, and performance gaps ... Develop scripts using Python, Bash, or PowerShell * Automate data pulls, file processing, and ...

Python (data analysis, ML libraries) * SQL and data manipulation at scale * Advanced analytics and BI tools * Experience with model evaluation and experimentation * Strong analytical and critical ...

Working knowledge of Python, R Studio or other data tools is a plus. * Experience with ERP and ... Bachelor's degree in Analytics, Finance, Economics or related field. * Experience in data-driven ...

Working knowledge of Python, R Studio or other data tools is a plus. * Experience with ERP and ... Bachelor's degree in Analytics, Finance, Economics or related field. * Experience in data-driven ...

Stefanini is looking for a Data Analyst in Greensboro, NC (Onsite) For quick apply, please reach ... Working knowledge of Python, R Studio or other data tools is a plus. Experience with ERP and ...

New

Experience with Python for data analysis or automation is a plus. * Knowledge of data governance, data privacy, and best practices is a plus. * Strong analytical, problem-solving, and troubleshooting ...

We are seeking a data visualization expert with a passion for transforming complex data into clear ... Experience in Python and advanced analytics * Demonstrated experience building executive-ready ...

We are seeking a data visualization expert with a passion for transforming complex data into clear ... Experience in Python and advanced analytics * Demonstrated experience building executive-ready ...

Primary Talent Partners has a new contract opening for a Data Analyst I with a large power and ... tools (Python, PowerShell, etc.) Company : Primary Talent Partners is a staffing agency that ...

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Python Data Analyst information

See North Carolina salary details

$30.9K

$75.1K

$123.6K

How much do python data analyst jobs pay per year?

As of Jun 12, 2026, the average yearly pay for python data analyst in North Carolina is $75,103.00, according to ZipRecruiter salary data. Most workers in this role earn between $56,800.00 and $88,200.00 per year, depending on experience, location, and employer.

What does a Python Data Analyst do?

A Python Data Analyst leverages the Python programming language to collect, process, and analyze large sets of data. They use tools and libraries like Pandas, NumPy, and Matplotlib to clean data, perform statistical analysis, and create visualizations that help organizations make data-driven decisions. Their role often involves extracting insights from complex datasets, automating data workflows, and communicating findings to stakeholders through reports or dashboards. Python Data Analysts play a crucial part in turning raw data into actionable business intelligence.

How do Python Data Analysts typically collaborate with other departments within an organization?

Python Data Analysts often work closely with teams such as marketing, finance, and product development to provide data-driven insights that inform business decisions. They regularly participate in cross-functional meetings to understand departmental objectives, gather requirements for data analysis, and present their findings in an accessible manner. Effective communication and the ability to translate technical results into actionable recommendations are essential, as analysts often act as a bridge between technical data and non-technical stakeholders.

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

AspectPython Data AnalystData Scientist
Required SkillsPython, SQL, data visualization, statistical analysisPython, R, machine learning, statistical modeling
Work EnvironmentBusiness analytics, reporting, data cleaningAdvanced modeling, predictive analytics, research
Industry UsageFinance, marketing, healthcare, retailTech, finance, research, AI development

While both roles require Python and data analysis skills, Data Scientists typically engage in more complex modeling and machine learning, whereas Python Data Analysts focus on data cleaning, visualization, and reporting to support business decisions.

What Does a Python Data Analyst Do?

As a Python data analyst, you use the Python programming language to develop tools for data mining, analysis, and data visualization. You typically develop a script to meet the specific data needs of your client or employer. Then, you test your code and perform debugging duties before deploying it in a live environment. Some data analysts also have algorithm creation responsibilities. In this case, after creating and testing an algorithm, you use Python with your algorithm to interpret data. You also develop reports to show to your clients or employers, and you may code a web app or interface that clients can use to visualize data sets.

Are Python coders still in demand?

Python data analysts are currently in high demand due to the language's versatility in data analysis, machine learning, and automation. Skills in libraries like Pandas, NumPy, and experience with data visualization tools increase employability across various industries.

Is 40 too old to become a data analyst?

Age is not a barrier to becoming a data analyst. Many professionals successfully transition into data analysis at various ages by acquiring skills in programming languages like Python or SQL, and gaining experience with data visualization tools. Employers value skills and experience over age, and continuous learning can help you stay competitive in the field.

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

To thrive as a Python Data Analyst, you need strong analytical skills, a solid grasp of statistics, and proficiency in Python programming, often supported by a degree in data science, mathematics, or a related field. Familiarity with data analysis libraries like pandas and NumPy, visualization tools such as Matplotlib or Seaborn, and experience with data querying languages like SQL are typically required. Attention to detail, critical thinking, and effective communication help you derive insights and present findings clearly to stakeholders. These skills and qualities are vital for transforming raw data into actionable business intelligence and supporting data-driven decision-making.

Is Python useful for data analysts?

Python is highly useful for data analysts as it offers powerful libraries like Pandas, NumPy, and Matplotlib for data manipulation, analysis, and visualization. It is widely used in the industry for automating tasks, building data pipelines, and performing statistical analysis, making it a valuable skill for the role.

Will AI replace data analysts?

AI is transforming the role of data analysts by automating routine tasks such as data cleaning and basic analysis, but it is unlikely to fully replace them. Data analysts are needed to interpret complex insights, make strategic decisions, and develop models that require domain expertise and critical thinking. Skills in programming, data visualization, and understanding AI tools remain valuable in this evolving field.
What are the most commonly searched types of Python Data Analyst jobs in North Carolina? The most popular types of Python Data Analyst jobs in North Carolina are:
What are popular job titles related to Python Data Analyst jobs in North Carolina? For Python Data Analyst jobs in North Carolina, the most frequently searched job titles are:
What job categories do people searching Python Data Analyst jobs in North Carolina look for? The top searched job categories for Python Data Analyst jobs in North Carolina are:
What cities in North Carolina are hiring for Python Data Analyst jobs? Cities in North Carolina with the most Python Data Analyst job openings:
Senior Python Data Engineer #3606832

Senior Python Data Engineer #3606832

Axiom Path

Charlotte, NC โ€ข Hybrid

$75 - $80/hr

Full-time

Posted 15 days ago


Job description

Be Part Of A High-Performing Team:

Join a technology team supporting a leading financial services environment where data-driven systems, scalable applications, and reliable engineering practices are critical to business operations. This team works across technical and business groups to build solutions that collect, process, and deliver large volumes of data for analysis, reporting, and downstream application needs. The environment is collaborative, fast-moving, and suited for a senior engineer who can work independently while partnering closely with cross-functional stakeholders.

What's In Store For You:

Engagement: W2 only (no C2C/1099)

This is a hybrid opportunity based in Charlotte, NC, supporting a long-term technical initiative within a financial services technology group. The role offers exposure to back-end engineering, ETL development, APIs, cloud data tooling, and enterprise-scale data workflows.

How You Will Make An Impact

  • Build and maintain scalable data pipelines that gather, transform, store, and process large volumes of data.
  • Develop server-side applications, APIs, scripts, and back-end components using Python and C#.
  • Support ETL development, data quality checks, and optimization of data storage and processing workflows.
  • Integrate databases, third-party services, cloud data tools, and internal APIs into reliable application solutions.
  • Write clean, efficient, well-documented code and participate in unit testing, debugging, and code reviews.
  • Collaborate with business and technical teams to gather requirements, implement solutions, and support CI/CD delivery practices.

Are you an experienced Python data engineering professional ready to make an impact?

  • 10+ years of senior-level software engineering, data engineering, or back-end development experience.
  • Strong hands-on Python development experience, ideally in data-heavy, API-driven, or enterprise back-end environments.
  • Strong SQL skills with experience working across relational databases and large datasets.
  • Experience developing ETL pipelines and supporting data quality, transformation, and storage optimization.
  • Hands-on experience with cloud data tools such as AWS Glue, Azure Data Factory, or comparable platforms.
  • C# development experience for server-side applications, APIs, or enterprise integrations.
  • Experience writing unit tests, debugging applications, participating in code reviews, and supporting CI/CD workflows.
  • Strong analytical thinking, documentation discipline, and ability to work independently or within Agile teams.
  • Financial services or capital markets experience is a plus.

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