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Weekend Python Data Analyst Jobs in McAllen, TX (NOW HIRING)

AMB Sports & Entertainment

Data Engineer

Mercedes, TX · On-site

$107K - $129K/yr

You'll partner closely with analysts and stakeholders to turn questions into durable data products ... Develop and maintain production-grade Python applications and scripts for data transformation, API ...

Varsity Tutors

Data Science Tutor

Edinburg, TX · Remote

$18 - $40/hr

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

SynergisticIT

Java React Full Stack Developer

Mcallen, TX · On-site

$50 - $64.50/hr

Currently, we are looking for entry-level software programmers, Java full stack developers, Python/Java developers, data analysts/data scientists, machine learning engineers for full time positions ...

Varsity Tutors

Business Analytics Tutor

Edinburg, TX · Remote

$18 - $40/hr

Adapts instruction using Excel, Tableau, Python, or R with real business data sets and case studies to support undergraduate and MBA students developing analytical capabilities for modern business ...

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All JobsWeekend Python Data Analyst JobsWeekend Python Data Analyst Jobs in McAllen, TX

Weekend Python Data Analyst information

See McAllen, TX salary details

$32.3K

$78.5K

$129.2K

How much do weekend python data analyst jobs pay per year?

As of Jun 24, 2026, the average yearly pay for weekend python data analyst in McAllen, TX is $78,510.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,400.00 and $92,200.00 per year, depending on experience, location, and employer.

What are some common challenges faced by Weekend Python Data Analysts, and how can they be managed?

Weekend Python Data Analysts often face challenges such as limited time to access stakeholders or full datasets, since many team members may not be available outside standard business hours. To manage these challenges, it’s important to communicate needs and data access requirements ahead of time, and to document findings thoroughly for seamless handovers. Being self-sufficient with Python tools and data wrangling is critical, as you may need to troubleshoot issues independently. Proactively setting clear goals for each shift can also help maximize productivity during weekend hours.

What are Weekend Python Data Analysts?

Weekend Python Data Analysts are professionals who work part-time or on weekends to analyze data using Python programming. They typically handle tasks such as cleaning data, performing statistical analyses, creating data visualizations, and generating reports. These analysts often support organizations that require flexible staffing or have projects that need attention outside of regular business hours. Their expertise in Python enables them to efficiently manipulate large datasets and extract actionable insights. This role is ideal for those seeking flexible work arrangements or supplementary income in the data analytics field.

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

To thrive as a Weekend Python Data Analyst, you need strong analytical skills, proficiency in Python programming, and a background in statistics or data science—often supported by a relevant degree or certification. Familiarity with data visualization tools (like Tableau or Power BI), SQL databases, and Python libraries such as Pandas and NumPy is typically expected. Excellent problem-solving, time management, and communication skills help you interpret data insights and present findings effectively during limited weekend hours. These skills ensure accurate data analysis, actionable recommendations, and efficient collaboration, even within a compressed work timeframe.

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

AspectWeekend Python Data AnalystWeekend Data Scientist
Required SkillsPython, data analysis, visualization, SQLPython, machine learning, statistical modeling, data analysis
CertificationsData analysis certifications, Python certificationsData science certifications, Python certifications
Work EnvironmentPart-time, project-based, remote or on-sitePart-time, project-based, remote or on-site
Industry UsageBusiness analytics, finance, marketingResearch, AI development, advanced analytics

Weekend Python Data Analysts focus on data cleaning, visualization, and basic analysis using Python, suitable for business insights. Weekend Data Scientists handle more complex modeling and machine learning tasks, often requiring advanced statistical skills. Both roles are part-time, flexible, and commonly used across industries, but Data Scientists typically require a deeper technical background.

What are the most commonly searched types of Python Data Analyst jobs in McAllen, TX? The most popular types of Python Data Analyst jobs in McAllen, TX are:
Weekend Python Data Analyst jobs near you
Data Engineer

Data Engineer

AMB Sports & Entertainment

Mercedes, TX • On-site

$107K - $129K/yr

Full-time

Posted yesterday

Job description

As a Data Engineer, you will own key parts of the pipeline lifecycle-from ingesting source data through transformation, testing, and publishing trusted datasets for downstream consumers. You'll partner closely with analysts and stakeholders to turn questions into durable data products, improve reliability and observability, and help standardize patterns that scale across teams. Success in this role looks like dependable pipelines, well-modeled data, and faster delivery of insights.

Responsibilities:

  • Design, develop, and maintain robust, scalable data pipelines and ETL/ELT workflows to support analytics, reporting, and machine learning initiatives
  • Build and optimize data models (dimensional, relational) across structured and semi-structured data sources including ticketing, fan engagement, broadcasting, and sponsorship data
  • Develop and maintain production-grade Python applications and scripts for data transformation, API integrations, and automation
  • Engineer solutions on Databricks or Snowflake for large-scale data processing, lakehouse architecture, and advanced analytics
  • Build and deploy serverless data solutions using Azure Functions for event-driven processing and microservice integrations
  • Design and implement data orchestration workflows using platforms such as Apache Airflow and/or Astronomer to ensure reliable, monitored, and scalable pipeline execution
  • Manage version control, CI/CD pipelines, and collaborative development workflows using Git-based platforms (GitHub, Azure DevOps)
  • Collaborate with data analysts, data scientists, and business stakeholders to translate requirements into technical solutions
  • Implement data quality frameworks, monitoring, and alerting to ensure data integrity and reliability across the platform
  • Contribute to the evolution of the data platform architecture, advocating for best practices in performance, security, and scalability
  • Participate in code reviews to uphold engineering standards

Qualifications:

  • Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field (or equivalent professional experience)
  • 3+ years of professional experience in data engineering or a related discipline
  • Strong relational database experience, including data modeling (star schema, snowflake schema, 3NF) and advanced SQL development (T-SQL, PL/SQL, or equivalent)
  • Proficiency in Python development for data engineering use cases (pandas, PySpark, API development, scripting, testing)
  • Hands-on experience with Databricks or Snowflake for data lakehouse/warehouse architecture and large-scale data processing
  • Experience building and deploying Azure Functions or similar serverless compute for data workflows
  • Working knowledge of Git-based platforms such as GitHub or Azure DevOps for version control, branching strategies, and CI/CD pipelines
  • Experience with data orchestration platforms such as Apache Airflow and/or Astronomer for pipeline scheduling, monitoring, and dependency management
  • Strong understanding of data warehousing concepts, ETL/ELT patterns, and data integration best practices
  • Excellent communication and collaboration skills with the ability to work cross-functionally in a fast-paced environment

Preferred Qualifications:

  • Industry certifications demonstrating proficiency in data engineering (e.g., Databricks Certified Data Engineer, Azure Data Engineer Associate DP-203, Snowflake SnowPro Core, Google Professional Data Engineer, AWS Data Engineer Associate)
  • Experience with a major cloud platform (Azure, AWS, or GCP) including infrastructure-as-code and cloud-native data services
  • Prior experience in sports, entertainment, media, or live events industries
  • Familiarity with streaming and real-time data technologies (Kafka, Event Hubs, Spark Structured Streaming)
  • Experience with data governance, cataloging, and lineage tools (Unity Catalog, Purview, Collibra)
  • Exposure to machine learning pipelines and MLOps practices
  • Experience with containerization (Docker, Kubernetes) and microservices architecture.

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