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Python Data Jobs in New York (NOW HIRING)

Python Data Integration Developer

Manhattan, NY ยท On-site

$55.25 - $76.25/hr

Python Data Integration Developer Basic Information * Experience Level: 5-10 years Required Skills * Strong Python 3.x experience for data ingestion and transformation. * DataFrame processing ...

Past experience building Python data APIs * Experience writing data validations in Python * Systematic experience required * Keen sense of finding data issues. * Experience with one of the following ...

Past experience building Python data APIs * Experience writing data validations in Python * Systematic experience required * Keen sense of finding data issues. * Experience with one of the following ...

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Python Data information

See New York salary details

$14

$64

$94

How much do python data jobs pay per hour?

As of Jul 9, 2026, the average hourly pay for python data in New York is $64.13, according to ZipRecruiter salary data. Most workers in this role earn between $52.88 and $72.84 per hour, depending on experience, location, and employer.

What is the salary for Python data analytics?

The salary for Python data analysts typically ranges from $60,000 to $100,000 annually, depending on experience, location, and industry. Professionals with strong skills in data manipulation, visualization, and tools like Pandas and SQL tend to earn higher salaries.

What Python jobs are in demand?

Python data-related jobs in demand include data analyst, data scientist, machine learning engineer, and backend developer. These roles often require proficiency in libraries like Pandas, NumPy, and frameworks such as TensorFlow, with employers seeking strong programming skills and experience with data analysis or AI projects.

What are some common challenges faced by Python Data professionals when working with large datasets?

Python Data professionals often encounter challenges such as optimizing code to handle large volumes of data efficiently and managing memory usage to prevent slowdowns or crashes. Working with big datasets may require leveraging tools like pandas, NumPy, or Dask, and sometimes integrating with distributed computing systems such as Apache Spark. Additionally, ensuring data quality and managing data pipelines for consistent and accurate results can be demanding. Collaborating closely with data engineers, analysts, and other stakeholders is common to ensure smooth data flow and analysis.

What is a Python Data professional?

A Python Data professional is someone who uses the Python programming language to analyze, process, and interpret data. They work with large datasets, perform data cleaning and transformation, and apply statistical or machine learning techniques to extract insights. These professionals often work in roles such as data analyst, data scientist, or data engineer, and use Python libraries like Pandas, NumPy, and scikit-learn to accomplish their tasks.

Will AI replace Python devs?

Python developers are unlikely to be fully replaced by AI, as their role involves designing, coding, and maintaining complex software systems that require human judgment and creativity. AI tools can assist with tasks like code generation and debugging, but human oversight remains essential for quality and innovation. Staying updated with new frameworks and machine learning techniques can help Python developers remain valuable in the evolving tech landscape.

What is the difference between Python Data vs Data Analyst?

AspectPython DataData Analyst
Required SkillsPython programming, data manipulation, scriptingExcel, SQL, data visualization
CertificationsPython certifications, data science coursesData analysis certifications, Excel certifications
Work EnvironmentData science teams, programming-heavy rolesBusiness intelligence, reporting teams
Industry UsageTech, finance, healthcareRetail, marketing, finance

Python Data roles focus on programming, data manipulation, and building data pipelines using Python, while Data Analysts primarily analyze data using tools like Excel and SQL to generate reports and insights. Both roles often collaborate but differ in technical depth and tools used.

What type of jobs can I get with Python?

Python is used in a variety of roles including software developer, data analyst, data scientist, machine learning engineer, and automation engineer. These jobs often require knowledge of libraries like Pandas, NumPy, and frameworks such as TensorFlow or Django, and may involve working in environments like cloud platforms or data centers.

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

To thrive as a Python Data professional, you need strong programming skills in Python, a solid understanding of data structures, algorithms, and experience with data analysis or data science, typically supported by a relevant degree. Familiarity with technical tools such as pandas, NumPy, SQL, Jupyter Notebooks, and often cloud platforms or machine learning frameworks is important, and certifications like Microsoft or Google Data certifications can be advantageous. Strong analytical thinking, attention to detail, and effective communication help you extract insights from data and collaborate with stakeholders. These skills and qualities are essential to efficiently process, analyze, and interpret data, driving informed business decisions.
What are popular job titles related to Python Data jobs in New York? For Python Data jobs in New York, the most frequently searched job titles are:
Infographic showing various Python Data job openings in New York as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $133,398 per year, or $64.1 per hour.

Python Data Integration Developer

SysMind Tech

Manhattan, NY โ€ข On-site

$55.25 - $76.25/hr

Contractor

Re-posted 19 days ago


Job description

Python Data Integration Developer
Basic Information
  • Experience Level: 5-10 years

Required Skills
  • Strong Python 3.x experience for data ingestion and transformation.
  • DataFrame processing expertise (Polars preferred, Pandas acceptable).
  • Relational database modeling skills.
  • Familiarity with Geneva's data structures (output layouts, not platform config).
  • AWS (S3, ECS/Fargate, RDS - Postgres).
  • API consumption (GraphQL, REST, JSON).
  • Strong experience deploying Geneva in the Private Credit / Fund space, including multi-layer SPV/Fund structures.
  • Knowledge of Geneva securities.

Nice-to-Haves
  • Working Java knowledge for ORM integration.
  • Experience with Snowflake as a staging area.
  • Knowledge of bitemporal data models.
  • Workflow automation (BPMN tools).

Core Responsibilities
  • Ingest and transform Geneva output data (post-trade, portfolio, accounting) into internal ORM (Postgres + ORM).
  • Develop Python-based data importers for ingestion and transformation.
  • Assist in implementing Java components for ORM integration and bitemporal data model handling.
  • Map Geneva data to internal relational structures, ensuring accuracy and referential integrity.
  • Use GraphQL APIs to deliver data in standardized formats.
  • Collaborate with internal teams to enhance ingestion workflows and support reporting.
  • Document, maintain, and test ingestion processes.
  • Support AWS-hosted infrastructure for data pipelines (ECS/Fargate, S3, RDS).
  • Use Snowflake for temporary staging of rapidly evolving datasets when needed.