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Hadoop Python Jobs in Buffalo, NY (NOW HIRING)

Openkyber

Data Engineer

Buffalo, NY · On-site

$110K - $133K/yr

Strong experience with SQL, Python, or Scala * Hands-on with data pipeline tools: Apache Spark ... Hadoop, Hive, Presto, etc. If interested please share your resume @ joshnar@openkyber.com

Keybank

Business Analytics Sr Assoc

Buffalo, NY · On-site

$80K - $150K/yr

Work with large datasets - using standard tools such as Python, Hadoop, R, SQL, SAS and Google Cloud - to solve business problems; Analyze and resolve anomalies discovered when using quantitative ...

Geico

Senior Contact Center Data Engineer

Buffalo, NY

$102K - $139K/yr

... Python, R, SAS, .NET, M, or DAX. * 2+ years of experience using source control, DevOps tools, or ... Hadoop, Azure, AWS, or similar platforms. * 3+ years of experience with a BA/BS degree or 5+ years ...

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Hadoop Python information

See Buffalo, NY salary details

$10

$58

$71

How much do hadoop python jobs pay per hour?

As of Aug 26, 2026, the average hourly pay for hadoop python in Buffalo, NY is $58.02, according to ZipRecruiter salary data. Most workers in this role earn between $55.19 and $63.32 per hour, depending on experience, location, and employer.

What is a Hadoop Python developer?

A Hadoop Python developer is a software professional who specializes in using Python programming language to develop, implement, and maintain applications that process and analyze large datasets within the Hadoop ecosystem. They leverage Python libraries like PySpark to write scalable data processing scripts, interact with Hadoop components such as HDFS, and optimize big data workflows. These developers play a critical role in building data pipelines, performing data transformation, and supporting analytics projects in organizations that handle vast amounts of data.

What are the key skills and qualifications needed to thrive as a Hadoop Python developer?

To thrive as a Hadoop Python Developer, you need a strong understanding of distributed computing, Hadoop ecosystem components (like HDFS, MapReduce, Hive, or Pig), and advanced Python programming skills, often supported by a degree in computer science or related field. Familiarity with tools such as Apache Spark, Sqoop, and workflow schedulers (like Oozie or Airflow), along with experience in handling big data platforms, is typically required. Problem-solving abilities, attention to detail, and effective communication help developers collaborate with teams and translate business requirements into scalable data solutions. These skills and qualifications are essential for efficiently processing and analyzing large datasets, ensuring data reliability, and driving business insights.

How do Hadoop Python developers typically collaborate with data engineers and analysts on large-scale data projects?

Hadoop Python developers frequently work alongside data engineers and analysts to design, implement, and optimize data pipelines for handling vast datasets. They are responsible for writing Python scripts that interface with Hadoop components, ensuring data is processed efficiently and meets project requirements. Regular communication with data engineers helps align on infrastructure and architectural decisions, while close collaboration with analysts ensures data outputs are accurate and actionable. Agile methodologies and daily stand-ups are common, fostering teamwork and quick problem-solving.

What is the difference between Hadoop Python vs Hadoop Java Developer?

AspectHadoop PythonHadoop Java Developer
Required CredentialsPython programming skills, Hadoop certificationsJava programming skills, Hadoop certifications
Work EnvironmentData analysis, scripting, data pipeline developmentCore development, system integration, big data application coding
Industry UsageData science, analytics, machine learning projectsData infrastructure, platform development, system optimization

Hadoop Python and Hadoop Java Developer roles both involve working with Hadoop ecosystems, but Python focuses more on data analysis and scripting, while Java is geared towards core development and system integration. The choice depends on your programming expertise and career goals within big data environments.

What are jobs in Hadoop Python?

Jobs in Hadoop Python typically involve developing and maintaining data processing tasks using Python scripts within the Hadoop ecosystem. These roles often require knowledge of Hadoop frameworks like MapReduce or Spark, along with Python programming skills, to handle large-scale data analysis and processing tasks. They may also involve working with distributed systems and data pipelines in a big data environment.

What are popular job titles related to Hadoop Python jobs in Buffalo, NY?

For Hadoop Python jobs in Buffalo, NY, the most frequently searched job titles are:

What job categories do people searching Hadoop Python jobs in Buffalo, NY look for?

The top searched job categories for Hadoop Python jobs in Buffalo, NY are:

What cities near Buffalo, NY are hiring for Hadoop Python jobs?

Cities near Buffalo, NY with the most Hadoop Python job openings:

Hadoop Python jobs near you
Infographic showing various Hadoop Python job openings in Buffalo, NY as of August 2026, with employment types broken down into 1% Internship, 83% Full Time, 10% Part Time, and 6% Contract. Highlights an 76% Physical, 6% Hybrid, and 18% Remote job distribution, with an average salary of $120,672 per year, or $58 per hour.

Data Engineer

Openkyber

Buffalo, NY • On-site

$110K - $133K/yr

Full-time

Re-posted 25 days ago

Job description

 Job Title: Data Engineer
 Location: Rochester, NY

 Employment Type: Full-Time (W2 Only)
 

Job Description:

Key Responsibilities:

  • Design, build, and maintain scalable data pipelines for batch and real-time data processing
  • Develop ETL/ELT processes to ingest, transform, and store large volumes of structured and unstructured data
  • Work with data architects, analysts, and stakeholders to ensure data quality and accessibility
  • Optimize data workflows and troubleshoot pipeline failures or performance issues
  • Implement data governance, security, and compliance best practices
  • Collaborate with DevOps and cloud teams to deploy and monitor data solutions

Required Skills:

  • 8+ years of experience in data engineering or related roles
  • Strong experience with SQL, Python, or Scala
  • Hands-on with data pipeline tools: Apache Spark, Airflow, Kafka, NiFi, or similar
  • Expertise in cloud platforms: AWS (Glue, Redshift, S3), Azure (Data Factory, Synapse), or GCP (BigQuery, Dataflow)
  • Familiarity with data warehousing concepts and tools
  • Experience with version control (Git) and CI/CD pipelines
  • Strong problem-solving and communication skills

Preferred Qualifications:

  • Experience with Delta Lake, Snowflake, or Databricks
  • Knowledge of infrastructure-as-code tools like Terraform or CloudFormation
  • Familiarity with data security frameworks and compliance (HIPAA, GDPR, etc.)
  • Exposure to big data ecosystems: Hadoop, Hive, Presto, etc.

If interested please share your resume @ joshnar@openkyber.com