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Python Big Data Jobs (NOW HIRING)

Damco

Python - Pyspark Engineer

Pittsburgh, PA · On-site

Job Title Key skills: Spark, PySPark Python Big Data Architect Hadoop, Hive, Scala, Spark, PySPark. Airflow and Kafka experience preferred. CloudEra experience preferred Hive, PySpark, Python, Impala ...

Saransh Inc

GCP Data Engineer with Python

Dearborn, MI · On-site

$105K - $126K/yr

Role: GCP Data Engineer with Python Location: Dearborn, MI (4 days a week onsite) Job Type ... Exposure to Big Data ecosystems and distributed data processing. Nice to have Technical Skills:

Anveta

Python Developer with quartz

Jersey City, NJ · On-site

$60/hr

... Python, Big Data Processing, Administration, and Reporting suite of applications. Responsibilities Have a good understanding of the E2E process of the application Have a good understanding of all ...

Techno Talent Inc.

Big Data Developer

Rockville, MD · On-site

$54 - $70/hr

Onsite We are seeking an experienced Big Data Developer with strong expertise in Apache Spark, Hadoop, AWS, Python/Scala, and SQL to build and optimize large-scale data processing solutions. Required ...

Syntricate Technologies

PYTHON DEVELOPER + BIG DATA

$70/hr

PYTHON DEVELOPER + BIG DATA Charlotte, NC Hybrid, 2 days onsite 12 months Web Cam Interview $70/Hr on W2 In this contingent resource assignment, candidate may: * Consult on complex initiatives with ...

New

TestingXperts

Big data

Bellevue, WA · On-site

$59.75 - $77.50/hr

Big data Location: Bellevue, WA Must Have Skills (Top 3 technical skills only) * 1. Accumulo ... Accumulo, Spark, and Python. Desired years of experience*: Above 10+ years Education ...

Lorven Technologies

Big Data Engineer

Costa Mesa, CA · On-site

$59.75 - $79/hr

... Python, Hadoop, HDFS, Spark, MapReduce framework Good Scala, Pyspark, Java coding experience for ... Big Data Applications (API & Batch) on AWS Cloud using java/scala/kotlin, Cassandra, , Python ...

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Python Big Data information

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How much do python big data jobs pay per year?

As of Jun 25, 2026, the average yearly pay for python big data in the United States is $132,452.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,000.00 and $155,000.00 per year, depending on experience, location, and employer.

What is a Python Big Data engineer?

A Python Big Data engineer is a technology professional who uses the Python programming language to develop, maintain, and optimize systems that process large volumes of data, often referred to as 'big data.' They work with big data technologies like Hadoop, Spark, and data storage solutions to extract insights and support business decisions. Their responsibilities include building data pipelines, ensuring data quality, and collaborating with data scientists and analysts. Python Big Data engineers are skilled in both programming and data engineering, making them essential for handling large-scale data processing tasks.

What is the difference between Python Big Data vs Data Engineer?

AspectPython Big DataData Engineer
Required SkillsPython, Big Data tools (Hadoop, Spark), data processingPython, SQL, ETL, data pipeline development
Work EnvironmentData processing teams, analytics projectsData infrastructure, pipeline management
CertificationsBig Data certifications (Cloudera, Hortonworks)Data engineering certifications (Google Cloud, AWS)

Python Big Data specialists focus on processing large datasets using Python and Big Data tools, often working on analytics projects. Data Engineers build and maintain data pipelines and infrastructure, utilizing Python alongside SQL and cloud platforms. While both roles require Python skills, their focus areas and certifications differ, with Python Big Data emphasizing data processing and Data Engineering emphasizing data infrastructure development.

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

To thrive as a Python Big Data Engineer, a strong background in Python programming, data structures, and distributed systems is essential, often supported by a degree in computer science or related fields. Familiarity with big data tools such as Hadoop, Spark, Kafka, and cloud platforms, as well as relevant certifications, is typically required. Strong analytical thinking, problem-solving abilities, and effective communication skills help professionals stand out in this field. These competencies are crucial for designing scalable data solutions, collaborating across teams, and extracting valuable insights from large datasets.

How do Python Big Data professionals typically collaborate with data engineers and data scientists in a project setting?

Python Big Data professionals often serve as a bridge between data engineers, who focus on building and maintaining data pipelines, and data scientists, who analyze and interpret data. On a typical project, you might work closely with data engineers to ensure data is efficiently ingested, cleaned, and stored using scalable solutions like Hadoop or Spark. You'll also support data scientists by developing tools, scripts, or models that help them extract insights from large datasets. Effective communication and teamwork are key, as projects often require integrating codebases and aligning on data requirements and project goals.
More about Python Big Data jobs
What job categories do people searching Python Big Data jobs look for? The top searched job categories for Python Big Data jobs are:
Python Big Data jobs near you
Infographic showing various Python Big Data job openings in the United States as of June 2026, with employment types broken down into 3% As Needed, 40% Full Time, 55% Part Time, 1% Contract, and 1% Nights. Highlights an 83% Physical, 5% Hybrid, and 12% Remote job distribution, with an average salary of $132,452 per year, or $63.7 per hour.

Python Big Data Engineer

Techvilla Solutions

Hartford, CT

Full-time

Posted 5 days ago

Job description

We are seeking an experienced Python Big Data Engineer with strong expertise in Databricks, Python, and AWS to design, develop, and maintain scalable data engineering solutions. The ideal candidate will have hands-on experience building cloud-native data pipelines, implementing ETL processes, and developing robust data platforms in an AWS environment. Experience with infrastructure automation and modern application development is highly desirable.

Roles and Responsibilities
  • Design, develop, and optimize scalable data pipelines using Databricks and Python.
  • Build and maintain cloud-based data solutions on AWS.
  • Develop and enhance ETL/ELT workflows for processing large-scale datasets.
  • Implement data integration, transformation, and validation processes.
  • Collaborate with cross-functional teams to understand business and technical requirements.
  • Ensure data quality, reliability, security, and performance across platforms.
  • Automate cloud infrastructure provisioning and deployment using Terraform.
  • Support software engineering initiatives, including API and application development where required.
  • Troubleshoot production issues and optimize existing data processing workflows.
Required Qualifications
  • 8–10 years of overall IT experience with a strong focus on Data Engineering and Big Data technologies.
  • Hands-on experience with Databricks, Python, and AWS services.
  • Strong knowledge of ETL development, data modeling, and data pipeline architecture.
  • Experience working with large-scale structured and unstructured datasets.
  • Understanding of cloud-native architecture and distributed data processing.
  • Experience with version control systems and CI/CD practices.
  • Strong analytical, problem-solving, and communication skills.
Preferred Qualifications
  • Experience with Node.js development.
  • Hands-on experience with Terraform for Infrastructure as Code (IaC).
  • Familiarity with Agile/Scrum development methodologies.
Required Skills Must-Have Skills
  • Databricks
  • Python
  • AWS Cloud Services
Preferred Skills
  • Node.js
  • Terraform

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