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Senior Python Data Analysis Jobs in Tennessee (NOW HIRING)

EnableComp

Senior Data Analyst

Franklin, TN

$84K - $107K/yr

Support continuous improvement initiatives through data analysis and performance monitoring * Maintain working knowledge of business applications and support ongoing enhancements and optimization

EnableComp

Senior Data Analyst

Franklin, TN · On-site

$84K - $107K/yr

Support continuous improvement initiatives through data analysis and performance monitoring * Maintain working knowledge of business applications and support ongoing enhancements and optimization

Modea

Data Analyst II

Nashville, TN · On-site +1

Data Analysis and Reporting * Produce high-quality client deliverables, including initial ... Utilize SQL, Python, or R to query, clean, and transform large datasets, enabling detailed analyses ...

FOCUSPOINT

Data Analyst

Nashville, TN · On-site

$40 - $57/hr

You'll work directly with stakeholders, engineers, operators, and senior leaders to uncover trends ... Proficient in SQL and data manipulation tools such as Excel, Python, or R. * BI Tools Experience:

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Senior Python Data Analysis information

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

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 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 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 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 most commonly searched types of Python Data Analysis jobs in Tennessee? The most popular types of Python Data Analysis jobs in Tennessee are:
What are popular job titles related to Senior Python Data Analysis jobs in Tennessee? For Senior Python Data Analysis jobs in Tennessee, the most frequently searched job titles are:
What job categories do people searching Senior Python Data Analysis jobs in Tennessee look for? The top searched job categories for Senior Python Data Analysis jobs in Tennessee are:
Senior Python Data Analysis jobs near you

Senior Business Intelligence and Data Analyst

Smith and Wesson

Maryville, TN • On-site

Full-time

Posted 20 days ago

Job description

Senior Business Intelligence & Data Analyst
In-Office/Non-Remote in Maryville, TN
We are looking for a Modern BI / Data Warehouse Developer who can bridge traditional BI engineering (T-SQL, ETL, SSIS-nice to have) with modern cloud analytics patterns, including building scalable data pipelines into Microsoft Fabric and creating transformations using notebooks (Python/Pandas) and related tooling.
This role focuses on data ingestion, modeling, transformations, and semantic layer readiness. While the role will not be responsible for building production reports, the ideal candidate understands reporting needs well enough to design data models and semantic models that support analytics and self-service BI.
COMPETENCIES AND SKILLS:
  • Strong hands-on experience with T-SQL and relational data modeling.
  • Proven experience building ETL/ELT pipelines and supporting production data workflows.
  • Experience with Azure Data Factory (ADF) or comparable orchestration tools.
  • Experience building transformations using notebooks, including Python and Pandas (and/or Spark-based transformations as needed).
  • Strong understanding of:
  • modern data warehousing
  • dimensional modeling (facts/dimensions, SCDs, conformed dimensions)
  • performance fundamentals (indexes, partitioning concepts, query tuning as applicable)
  • Working knowledge of reporting concepts (requirements, visual performance considerations, data shaping), even if not building reports.
  • Nice to have skills:
  • TensorFlow, PyTorch, Hugging Face
  • SSIS experience (nice-to-have, not required).
  • Experience with Microsoft Fabric components (Lakehouse, Warehouse, pipelines, notebooks, shortcuts, etc.).
  • Familiarity with semantic modeling platforms and patterns (e.g., Power BI semantic models/tabular concepts).
  • Exposure to data governance, cataloging, and lineage practices.
  • Experience with CI/CD for data assets (Git integration, environment promotion).

ESSENTIAL DUTIES AND RESPONSIBILITIES:
  • Design and implement data ingestion pipelines to move data from source systems (SQL, files, APIs, SaaS apps) into Microsoft Fabric (e.g., Lakehouse/Warehouse).
  • Create and maintain pipelines using Azure Data Factory (ADF) and/or Fabric-native orchestration patterns as appropriate.
  • Build transformation logic using notebooks and modern approaches (Python, Pandas, Spark where applicable).
  • Apply best practices for:
    • data quality checks & validations
    • reproducibility (parameterization, modular notebooks, version control)
    • performance optimization (partitioning, pushdown, caching strategies where relevant)
  • Design and maintain enterprise data warehouse models
  • Understand how to prepare data for semantic models and analytics consumption:
  • Collaborate with report developers/analysts by ensuring data models align with real BI usage patterns.
  • Work closely with stakeholders (analysts, app teams, data owners) to translate requirements into scalable pipelines and models.
  • Participate in code reviews, documentation, and operational handoffs.
  • Help establish standards for naming, versioning, environments, and deployment patterns.

QUALIFICATIONS:
  • 3+ years of professional experience in BI, data engineering, or data warehouse development in an enterprise environment.
  • 2+ years of hands-on experience with T-SQL, including:
    • complex joins, window functions, CTEs
    • query optimization and performance tuning
    • building and maintaining transformation logic in SQL
  • 2+ years of experience designing and implementing ETL/ELT pipelines.
  • 1+ years of experience building data pipelines using Azure Data Factory (ADF) or a comparable orchestration tool.
  • 3+ years of experience with modern data warehousing principles, including:
    • layered architectures (raw, curated, consumption)
    • ELT patterns batch and incremental loading strategies
  • 3+ years of hands-on dimensional data modeling experience, including:
    • star and snowflake schemas
    • fact and dimension table design
    • surrogate keys and SCD (Type 1/2) patterns
  • 1+ years of experience developing data transformations using notebooks.
  • Working knowledge of reporting and analytics tools concepts (e.g., how analysts and business users consume data), even if not responsible for building reports directly.
  • Professional communications skills, both verbal and written. Good team player.
  • Manage personal workload and work under tight timeframes.
  • Must be able to work independently with minimal supervision.
  • Bachelor's degree in Computer Science, Engineering, or a related field preferred.

PHYSICAL DEMANDS:
  • Occasional: bending, kneeling, squatting, standing, walking, reaching, overhead reaching, and fine motor skills

WORK ENVIRONMENT:
  • Normal office environment and office lighting
  • Within the Smith & Wesson manufacturing facility employees may be exposed to manufacturing noise, airborne liquid chemicals, fine particulate dust, ambient temperatures, and industrial lighting
  • All employees are required to apply ergonomic correctness to all job tasks

Updated 5/22/26

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