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Senior Python Data Analysis Jobs (NOW HIRING)

SRP Systems Inc

Senior Python/Spark developer

Princeton, NJ · On-site

$127K - $171K/yr

Good data analysis skills * Any experience with Spark or Hadoop is a plus In this position, you will work as a senior Python developer and also as a data analyst, which involves reviewing data in our ...

SRP Systems Inc

Senior Python/Spark developer

Princeton, NJ · On-site

$127K - $171K/yr

Good data analysis skills * Any experience with Spark or Hadoop is a plus In this position, you will work as a senior Python developer and also as a data analyst, which involves reviewing data in our ...

Palnar

Sr. Python Data Engineer

Mclean, VA · On-site

Python, Java, Spark, SQL, Databricks, RESTful APIs, AWS Glue, ECS S3 The role is to continue to ... This work involves building pipelines to get data into the platform, update drools based rules, and ...

Redolent, Inc.

Senior Python Developer

Jersey City, NJ · On-site

$126K - $170K/yr

... data analysis • 7yr+ Years of experience in Risk and pricing application development, will be plus • 7yr+ Years of experience in REST, ReactJS or FullStack development • Experience and exposure ...

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

As of Aug 13, 2026, the average yearly pay for senior python data analysis in the United States is $141,976.00, according to ZipRecruiter salary data. Most workers in this role earn between $121,500.00 and $163,500.00 per year, depending on experience, location, and employer.

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 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.
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Senior Python Data Analysis jobs near you
Infographic showing various Senior Python Data Analysis job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $141,976 per year, or $68.3 per hour.

Senior Python Data Engineer

Accord Technologies Inc.

Hartford, CT • Remote

$117K - $140K/yr

Contractor

Re-posted 10 days ago

Job description

Job Title: Sr. Python Data Engineer (Python, MongoDB, PowerBI and Data Extraction, ability to write code)
Location: Hartford, CT
Position type: W2 contract 
Duration: 12+ months extendable.
Mandatory skills:
Strong Python candidate having exp in Mondo DB, PowerBI and Data ExtractionOverview

We are seeking a motivated and skilled Data Engineer to join our team. The ideal candidate will have strong proficiency in Python, knowledge of MongoDB, and experience with Power BI. This role will primarily focus on building data extracts and data feeds for downstream systems, including Ledger, Reporting, and Boudreaux. You will be responsible for writing the code necessary to deliver the required data based on predefined definitions

Responsibilities:

  •  Data Extraction and Transformation: Write efficient and scalable Python code to extract and transform data from various sources, ensuring it meets the requirements for downstream systems.
  • MongoDB Management: Utilize MongoDB for storing and managing data. Design and optimize data models and queries to ensure high performance and reliability.
  • Power BI Integration: Collaborate with stakeholders to deliver data in a format suitable for reporting and visualization in Power BI. Ensure that the data aligns with business needs and reporting requirements.
  • Data Feed Development: Develop and maintain data feeds for downstream systems, including Ledger and Boudreaux, ensuring timely and accurate data delivery.
  • Collaboration with Stakeholders: Work closely with business analysts and other stakeholders to understand data definitions and requirements, translating them into technical specifications.
  • Documentation: Maintain comprehensive documentation of data pipelines, data models, and technical specifications to support knowledge sharing and compliance.
  • Quality Assurance: Implement data validation and quality checks to ensure the accuracy and integrity of the data being delivered.

Requirements:

  • Bachelor’s degree in Computer Science, Data Engineering, Information Technology, or a related field.
  • Minimum of 9 years of experience in data engineering or a related field.
  • Strong experience in Python programming, particularly in data manipulation and ETL processes.
  • Solid knowledge of MongoDB and experience in database design and management.
  • Familiarity with Power BI for creating reports and dashboards.
  • Experience in building data extracts and feeds for business applications.
  • Analytical Skills: Strong analytical and problem-solving skills with a focus on delivering high-quality data solutions.
  • Communication: Excellent verbal and written communication skills, with the ability to clearly convey technical concepts to both technical and non-technical stakeholders.
  • Team Player: Ability to work collaboratively in a fast-paced, team-oriented environment.