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Python Analytics Jobs in Griffin, GA (NOW HIRING)

Lead Analytics Engineer

Griffin, GA · Remote

$80K - $115K/yr

Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. • Advanced proficiency in Python for data manipulation and analytics engineering ...

Proficiency in Python is preferred. * Understanding basic theories/math behind deep/machine ... Good analytical and communication skills Good to Have * Knowledge and experience with optical ...

... Python). • Understanding of IT security principles, especially in government or regulated environments. • Knowledge of ITIL and DevOps best practices. • Strong analytical, troubleshooting, and ...

Data Platform Engineer

Mcdonough, GA · On-site

$104K - $125K/yr

Data & Analytics Location: Hybrid Employment Type: Full-Time Position Overview We are seeking an ... Proficiency in Python for data engineering workloads; SQL expertise required. * Experience ...

Data Engineer

Fayetteville, GA · On-site +1

$100K - $120K/yr

Partner with BI and ML teams to support analytics and advanced data use cases * Identify ... strong Python, SQL, and Spark skills * Hands-on experience building and automating ETL/ELT ...

... Python, Shell, Ansible). Familiarity with CI/CD integration and DevOps practices for API platforms. Knowledge of monitoring and analytics for API performance and usage (e.g., Prometheus, Grafana)

... Python, Shell, Ansible). Familiarity with CI/CD integration and DevOps practices for API platforms. Knowledge of monitoring and analytics for API performance and usage (e.g., Prometheus, Grafana)

... Python, Shell, Ansible). Familiarity with CI/CD integration and DevOps practices for API platforms. Knowledge of monitoring and analytics for API performance and usage (e.g., Prometheus, Grafana)

... Python, Shell, Ansible). Familiarity with CI/CD integration and DevOps practices for API platforms. Knowledge of monitoring and analytics for API performance and usage (e.g., Prometheus, Grafana)

... Python, Shell, Ansible). Familiarity with CI/CD integration and DevOps practices for API platforms. Knowledge of monitoring and analytics for API performance and usage (e.g., Prometheus, Grafana)

Python Analytics information

See Griffin, GA salary details

$11

$51

$76

How much do python analytics jobs pay per hour?

As of Jun 23, 2026, the average hourly pay for python analytics in Griffin, GA is $51.94, according to ZipRecruiter salary data. Most workers in this role earn between $42.79 and $58.99 per hour, depending on experience, location, and employer.

What is the salary of a Python analyst?

The salary of a Python analyst typically ranges from $60,000 to $110,000 annually, depending on experience, location, and industry. Professionals with strong skills in data analysis, machine learning, and proficiency in tools like Pandas and Jupyter Notebook tend to earn higher salaries.

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

To thrive as a Python Analytics professional, you need a strong background in statistics, data analysis, and proficiency in Python programming, often supported by a degree in computer science, mathematics, or a related field. Familiarity with data analytics libraries (such as pandas, NumPy, and scikit-learn), data visualization tools, and experience with databases are typically required. Strong problem-solving, communication, and critical thinking skills help in interpreting data and conveying insights to stakeholders. These abilities are crucial for turning complex data into actionable business decisions and driving organizational success.

Is Python good for data analysts?

Python is widely used by data analysts due to its simplicity, extensive libraries like pandas and NumPy, and strong community support. It enables efficient data manipulation, analysis, and visualization, making it a valuable skill for the role.

Can I be a data analyst in 3 months?

Becoming a data analyst with a focus on Python typically requires several months of dedicated learning, including skills in data manipulation, visualization, and tools like pandas and SQL. While some individuals may acquire foundational skills in three months, gaining proficiency for a professional role usually takes longer and depends on prior experience and learning pace.

What is the difference between Python Analytics vs Data Analyst?

AspectPython AnalyticsData Analyst
Required SkillsPython programming, data manipulation, statistical analysisExcel, SQL, basic statistics
CertificationsPython certifications, data analysis coursesNone typically required, but certifications like CAP or Microsoft certifications are common
Work EnvironmentData science teams, analytics departments, tech companiesBusiness units, marketing, finance, consulting firms
ToolsPython libraries (Pandas, NumPy, scikit-learn)Excel, SQL, Tableau, Power BI

Python Analytics involves using Python programming to perform advanced data analysis, modeling, and automation, often requiring coding skills. Data Analysts focus on interpreting data using tools like Excel and SQL, providing reports and insights. While both roles analyze data, Python Analytics typically involves more technical and programming expertise, making it suitable for complex data projects and predictive modeling.

Is Python still in demand?

Python analytics roles remain highly in demand due to Python's versatility in data analysis, machine learning, and automation. Employers seek professionals skilled in libraries like Pandas, NumPy, and frameworks such as TensorFlow, often requiring proficiency in data visualization and scripting. Staying updated with Python versions and related tools enhances job prospects in this field.

What are some typical challenges faced by professionals in Python Analytics roles, and how can I prepare for them?

Professionals in Python Analytics roles often encounter challenges such as handling large and complex datasets, ensuring data quality, and communicating insights effectively to non-technical stakeholders. To prepare, it's beneficial to strengthen your skills in data cleaning, visualization libraries (like Matplotlib or Seaborn), and learn best practices for writing efficient, reproducible code. Collaborating closely with data engineers, business analysts, and decision-makers is also a key part of the job, so developing strong communication and teamwork abilities will help you succeed.

What is a Python Analytics professional?

A Python Analytics professional is someone who uses the Python programming language to collect, process, analyze, and interpret data in order to help organizations make data-driven decisions. They often work with large datasets, perform statistical analyses, create data visualizations, and build predictive models. These professionals may work in industries such as finance, healthcare, marketing, or technology, and typically use libraries like Pandas, NumPy, and Matplotlib. Their work helps businesses gain insights, optimize processes, and solve complex problems through data.
What are popular job titles related to Python Analytics jobs in Griffin, GA? For Python Analytics jobs in Griffin, GA, the most frequently searched job titles are:
Infographic showing various Python Analytics job openings in Griffin, GA as of June 2026, with employment types broken down into 91% Full Time, 7% Part Time, and 2% Contract. Highlights an 80% Physical, 6% Hybrid, and 14% Remote job distribution, with an average salary of $108,038 per year, or $51.9 per hour.
Lead Analytics Engineer

Lead Analytics Engineer

eShipping, LLC

Griffin, GA • Remote

$80K - $115K/yr

Full-time

Posted 16 days ago


Job description

Position Summary

The Lead Analytics Engineer serves as the primary analytics resource embedded within the Solutions team, bridging the gap between complex data systems and business decision-making. This role combines deep technical expertise in analytics engineering with a consultative partnership approach — translating business needs into well-structured data models, building scalable data pipelines, and equipping cross-functional stakeholders with the insights and tools they need to drive outcomes. The Lead Analytics Engineer also provides technical mentorship and guidance to peers, reviewing work for accuracy, and helping elevate the team's overall data maturity.

Essential Duties and Responsibilities

Duties include but are not limited to the following:

• Design, build, and maintain scalable data models, reusable datasets, and analytics-ready assets that support reliable reporting, self-service analysis, and downstream decision-making across the organization

• Use SQL expertly to query, validate, and optimize data workflows, serving as a bridge between business questions, source systems, and scalable analytics solutions

• Write and maintain Python-based data transformation logic, including production-grade PySpark pipelines, to manipulate, validate, and operationalize complex datasets at scale

• Implement and manage bronze/silver/gold data modeling patterns within a Delta Lake or comparable lakehouse architecture

• Partner directly with the Solutions team as an embedded analytics resource, proactively identifying opportunities to leverage data for operational improvements

• Translate business requirements into technical specifications and deliver actionable insights to non-technical stakeholders

• Guide other team members on analytics engineering best practices, data modeling standards, and technical approaches

• Review the work of others to ensure data accuracy, consistency, and adherence to established standards

• Read and tune established reporting solutions to diagnose and resolve performance issues

• Collaborate with engineering, operations, finance, and customer success teams to understand evolving data needs

• Evaluate, learn, and adopt new tools, platforms, and frameworks quickly, helping the team stay effective in a fast-evolving data environment

Specific Department Responsibilities

• Serve as point of contact between data engineering function and Solutions team, fostering an embedded partnership

• Proactively identify gaps in existing data models and reporting and recommend improvements

• Contribute to the development and evolution of the organization's data strategy, including architecture decisions, tooling, and governance standards

• Support the evaluation and adoption of new data technologies and platforms

• Create and maintain technical documentation for data models, pipelines, and processes

• Participate in code reviews and provide constructive, growth-oriented feedback to peers

• Communicate project status, technical trade-offs, and data insights to both technical and non-technical audiences

Required Skills and Abilities

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skills, and/or ability required. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions.

• Advanced proficiency in Python for data manipulation and analytics engineering, including writing clean, maintainable code to transform, validate, and operationalize complex datasets

• Expert-level proficiency in SQL, including window functions, CTEs, complex joins, MERGE operations, and query execution plan analysis, with the ability to use SQL as a bridge between business needs and scalable data solutions

• Familiarity with Delta Lake or comparable lakehouse technologies, including schema evolution, time travel, and medallion architecture patterns

• Demonstrated ability to quickly learn new tools, platforms, and frameworks, and become productive with emerging technologies in a fast-evolving data environment

• Demonstrated ability to translate complex business requirements into well-structured, scalable data models

• Excellent written and verbal communication skills, with ability to explain technical concepts to non-technical stakeholders

• Strong analytical and problem-solving skills with keen attention to detail

• Ability to work independently with minimal oversight while exercising sound judgment

• Comfortable mentoring others and providing technical guidance without direct management authority

• Ability to manage multiple priorities and adapt in a fast-paced environment

• Experience working with BI and visualization tools (e.g., Power BI, Apache Superset, or similar)

• Familiarity with cloud data platforms such as Apache Spark, Databricks, Azure Data Lake, or comparable environments

Minimum Education and Experience

• Bachelor's degree in Computer Science, Data Science, Information Systems, Statistics, or a related field — or equivalent practical experience

• 5+ years of professional experience in analytics engineering, data engineering, or a senior data analyst role with significant hands-on data modeling responsibilities

• Hands-on production experience with Apache Spark and PySpark

• Working experience with lakehouse architectures (Apache Spark or comparable)

• Track record of partnering directly with business teams (operations, finance, solutions, customer success, etc.) as a primary analytics resource

• Experience mentoring or guiding peers in a technical environment

• Freight, logistics, or transportation industry experience preferred

Physical Demands and Work Environment

The physical demands and work environment characteristics described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. This description reflects management’s assignment of essential functions; it does not proscribe or restrict the tasks that may be assigned.

• Physical Demands: While performing the duties of this job, the employee is regularly required to remain in a stationary position for at least 50% of the time. The employee needs to occasionally move about inside the office to access file cabinets, office machinery, etc. The general level of physical activity would be defined as sedentary. The employee is regularly required to operate a computer and other office productivity machinery, such as a calculator, telephone, copy machine, and printer. Some movements of the hands, arms, and wrists may involve repetitive motions. Specific vision abilities required by this job include the ability to detect, determine, perceive, identify, recognize, judge, observe, inspect, estimate, and assess various activities and surroundings.

• Cognitive/Mental Requirements: While performing the duties of this job, the employee is regularly required to comprehend and use basic language, either written or spoken, to communicate simple and complex information, ideas, and information. The employee is also required to use logic to define problems, collect information, establish facts, draw valid conclusions, interpret information, and deal with abstract variables for unique or unfamiliar situations. The employee must use problem-solving skills to formulate and apply appropriate courses of action for routine or familiar situations. The employee may be required to perform numerical operations including basic counting, adding, subtracting, multiplying, and dividing or more complex quantitative calculations.

• Work Environment: While performing the duties of this job, the employee is inside a central heat and air-conditioned office building. The noise level in the work environment is minimal.

Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of an employee. Duties, responsibilities, and activities may change at any time with or without notice.

eShipping is an Equal Opportunity Employer.