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Senior Python Data Analysis Jobs in Flower Mound, TX

Vets Hired

Python Developer

Irving, TX · On-site

$48.25 - $66.50/hr

We are seeking a highly skilled and experienced Senior Python Developer. The ideal candidate will ... Hands-on experience with Grafana for monitoring and data visualization. * Solid understanding of ...

Virtusa

Gen AI developer

Irving, TX · On-site

$116K - $157K/yr

... This is a senior development role responsible for leading the design, architecture, and ... The role requires deep expertise in Python, data engineering, and AI/GenAI (including LLMs), with a ...

Vst

Senior Data Analyst

Irving, TX · On-site

$82K - $104K/yr

Job Summary As Senior Data Analyst, you will be responsible for leading data analysis projects and ... advanced analysis using statistical tools and software, such as SQL or Python. Designing and ...

Vistra Energy

Senior Data Analyst

Irving, TX · On-site

$82K - $104K/yr

Job Summary As Senior Data Analyst, you will be responsible for leading data analysis projects and ... advanced analysis using statistical tools and software, such as SQL or Python. Designing and ...

TXU Energy

Senior Data Analyst

Irving, TX · On-site

$82K - $104K/yr

Job Summary As Senior Data Analyst, you will be responsible for leading data analysis projects and ... advanced analysis using statistical tools and software, such as SQL or Python. Designing and ...

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Senior Python Data Analysis information

See Flower Mound, TX salary details

$50.4K

$130.2K

$178.9K

How much do senior python data analysis jobs pay per year?

As of Sep 9, 2026, the average yearly pay for senior python data analysis in Flower Mound, TX is $130,228.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,400.00 and $150,000.00 per year, depending on experience, location, and employer.

What is a senior Python data analyst?

A Senior Python Data Analyst is an experienced professional who uses Python programming to collect, process, and analyze large sets of data. They are responsible for extracting meaningful insights from data to support business decisions, often using libraries like pandas, NumPy, and matplotlib. In addition to technical skills, they also apply statistical analysis and data visualization techniques, and frequently mentor junior analysts or collaborate with data scientists and engineers. Their role may also involve developing automated data pipelines and ensuring data quality across projects.

What are the key skills and qualifications needed to thrive as a senior Python data analyst?

To thrive as a Senior Python Data Analyst, you need an in-depth understanding of data analysis, statistical modeling, and advanced Python programming, typically supported by a degree in a quantitative field. Proficiency with data analysis libraries (like pandas, NumPy, and SciPy), visualization tools (such as Matplotlib and Seaborn), and experience with SQL databases are essential, and certifications like Microsoft Certified: Data Analyst Associate can be beneficial. Strong problem-solving abilities, effective communication, and the capacity to distill complex data insights for stakeholders are critical soft skills. These competencies enable you to extract actionable insights from large datasets, drive data-informed decision-making, and collaborate effectively across teams.

What are some common challenges senior Python data analysts face when working with large datasets, and how can they overcome them?

Senior Python Data Analysts often encounter difficulties such as slow processing speeds, memory limitations, and data quality issues when handling large datasets. To overcome these challenges, it's essential to leverage efficient libraries like pandas and Dask, utilize optimized data formats (such as Parquet), and implement batch processing or cloud-based solutions. Collaborating closely with data engineers and IT teams also helps ensure robust data pipelines and infrastructure. Regular code optimization and staying updated on best practices can further enhance performance when working at scale.

What is the difference between Senior Python Data Analysis vs Data Scientist?

AspectSenior Python Data AnalysisData Scientist
Required SkillsPython, SQL, data visualization, statistical analysisPython, R, machine learning, statistical modeling
Work EnvironmentData analysis teams, business unitsResearch, product development, analytics teams
Industry UsageBusiness intelligence, finance, marketingTech, healthcare, finance, research
CertificationsPython certifications, data analysis coursesData science certifications, machine learning courses

While both roles involve Python and data handling, Senior Python Data Analysts focus on interpreting data and creating reports for business decisions, whereas Data Scientists develop predictive models and advanced algorithms to extract deeper insights. The roles often overlap, but Data Scientists typically require broader skills in machine learning and statistical modeling.

What are the most commonly searched types of Python Data Analysis jobs in Flower Mound, TX?

The most popular types of Python Data Analysis jobs in Flower Mound, TX are:

What are popular job titles related to Senior Python Data Analysis jobs in Flower Mound, TX?

For Senior Python Data Analysis jobs in Flower Mound, TX, the most frequently searched job titles are:

What job categories do people searching Senior Python Data Analysis jobs in Flower Mound, TX look for?

The top searched job categories for Senior Python Data Analysis jobs in Flower Mound, TX are:

What cities near Flower Mound, TX are hiring for Senior Python Data Analysis jobs?

Cities near Flower Mound, TX with the most Senior Python Data Analysis job openings:

Senior Python Data Analysis jobs near you
Infographic showing various Senior Python Data Analysis job openings in Flower Mound, TX as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $130,228 per year, or $62.6 per hour.

Senior Python/QA Engineer

Addison, TX • On-site

Long Finch Technologies
IT Services • 51 - 200 employees
Learn more about Long Finch Technologiesexternal

Full-time

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

Job description

We are seeking an experienced Senior Python/QA Engineer to serve as a quality gatekeeper across the full software delivery lifecycle. The ideal candidate will have strong expertise in Python automation, Playwright, Selenium, API testing, data validation, and CI/CD, along with experience testing modern data platforms such as Databricks and Snowflake.

Key Responsibilities
  • Develop and execute comprehensive Test Strategies, Test Plans, Test Cases, and Test Scenarios.
  • Review Business Requirements Documents (BRDs) and map requirements to testable acceptance criteria.
  • Identify requirement gaps, ambiguities, and potential quality risks before development begins.
  • Maintain a Requirements Traceability Matrix (RTM) linking BRD requirements, test cases, and test results.
  • Participate in BRD walkthroughs, requirement reviews, and stakeholder sign-off meetings.
  • Design and execute end-to-end tests covering the complete data pipeline from source systems through Databricks/Snowflake transformations to dashboard UI.
  • Validate data accuracy across Databricks Unity Catalog schemas.
  • Develop and execute SQL-based data validation scripts.
  • Build Python-based data quality and regression frameworks using Great Expectations, Deequ, or custom frameworks.
  • Validate data completeness, referential integrity, schema evolution, and data consistency across raw and curated layers.
  • Develop scalable automation frameworks using Python, Playwright, and Selenium WebDriver.
  • Perform functional, integration, regression, and end-to-end testing.
  • Conduct comprehensive REST and GraphQL API testing.
  • Validate API contracts including request/response schemas, status codes, headers, authentication, and authorization.
  • Use tools such as Bruno, Postman, Requests, HTTPX, and Swagger/OpenAPI for API validation and automation.
  • Test authentication and authorization workflows, including token validation, role-based access, and session management.
  • Validate API error handling, malformed payloads, rate limiting, timeout behavior, and 4xx/5xx responses.
  • Perform API performance and load testing using Locust, k6, or JMeter.
  • Validate API versioning, backward compatibility, and deprecation scenarios.
  • Automate API contract testing within CI/CD pipelines to identify breaking changes before deployment.
  • Validate consistency between API responses and underlying Databricks/SQL query results.
  • Track defects through resolution and ensure requirements are fully validated with no escaped defects.
  • Collaborate with developers, business stakeholders, data engineers, and other QA teams in a global delivery environment.
Required Skills & Qualifications
  • 8+ years of experience in Python and QA/automation testing.
  • Strong hands-on experience with Python automation.
  • Strong expertise in Playwright using Python, TypeScript, or JavaScript.
  • Strong experience with Selenium WebDriver.
  • Hands-on experience with API testing and API automation.
  • Strong experience with REST and GraphQL APIs.
  • Strong experience with SQL and data validation.
  • Experience testing Databricks, Unity Catalog, Snowflake, and modern data pipelines.
  • Experience building scalable automation frameworks.
  • Experience with Great Expectations, Deequ, or custom data quality frameworks.
  • Strong experience with CI/CD and DevOps practices.
  • Hands-on experience with Docker, Azure DevOps, Jenkins, and GitHub Actions.
  • Strong understanding of functional, integration, regression, system, and end-to-end testing.
  • Experience with Test Strategy, Test Planning, Test Case Design, and Test Execution.
  • Strong experience with Requirements Traceability and Defect Management.
  • Strong analytical, troubleshooting, and problem-solving skills.
  • Excellent communication and stakeholder collaboration skills.
  • Exposure to Generative AI / Agentic AI testing is a plus.

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