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Hadoop Python Jobs in Ontario (NOW HIRING)

The technology platform spans the breadth of Linux and Cloud environments, Python, Big data/Hadoop and ML platforms. Leads and hands on in the quality control and QE testing of cross-functional ...

... Hadoop, Computer Programming, DevOps, GitHub, GitHub Copilot, Leadership, Python (Programming Language), Structured Query Language (SQL), Test Automation Additional Job Details Address: RBC WATERPARK ...

The ideal candidate will have a solid foundation in Python, with exposure to Spark, Hadoop, and cloud platforms considered a strong asset. This role offers hands-on experience, mentorship, and ...

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Hadoop Python information

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 job categories do people searching Hadoop Python jobs in Ontario look for?

The top searched job categories for Hadoop Python jobs in Ontario are:

Infographic showing various Hadoop Python job openings in Ontario as of August 2026, with employment types broken down into 1% Internship, 83% Full Time, 11% Part Time, and 5% Contract. Highlights an 76% Physical, 6% Hybrid, and 18% Remote job distribution.

Data DevOps Engineer

Toronto, ON

Full-time

Posted 9 days ago


Job description

Our purpose – Opening up a world of opportunity – explains why we exist. Here at HSBC, we use our unique expertise, capabilities, breadth and perspectives to open new kinds of opportunity for our more than 40 million customers. We’re bringing together the people, ideas, and capital that nurture progress and growth, helping to create a better world – for our customers, our people, our investors, our communities, and the planet we all share.  

In Canada, HSBC Global Services (Canada) Limited (HGCA) is a wholly owned subsidiary of HSBC Global Services Limited. Operating in Toronto and Vancouver, HGCA is part of a global service company, delivering services to support the operating entities of HSBC Group. We have different capabilities that provide tools and processes to facilitate the functions, business, and entities with their service management responsibilities. 

Chief Technology Office (CTO) Data Technology is a data-driven shared service organization committed to unlocking value from data to serve our customers. We are a unified data technology team with a diverse organization of more than 3,000 colleagues across multiple global locations. We are transforming data technology into an Enterprise Shared Service Capability delivery model that will scale across key Global and Regional business markets.

Our CTO Analytics Technology team is at the forefront of developing cutting-edge data science platforms across multi-cloud environments. We leverage advanced analytics and data-driven insights to enhance our services and drive business growth.

We are looking for a passionate and driven Data Development and Operations (Data DevOps) Engineer to join our CTO Analytics Technology team. In this role, you will work on a state-of-the-art data science platform, collaborating with data engineers, data scientists, and other stakeholders to optimize data workflows and enhance our analytics capabilities across multi-cloud environments.

As our Data DevOps Engineer you will:

  • Assist in the development, deployment, and maintenance of data pipelines and workflows using Big Data technologies such as Apache Hadoop (Hadoop), Hadoop Distributed File System (HDFS), Google BigQuery (BigQuery), Amazon EMR (EMR), Snowflake, and Databricks
  • Support data science initiatives by utilizing tools such as JupyterHub, MLflow, Google Vertex AI (Vertex AI), Google Cloud Dataproc (Dataproc), Google Cloud Dataflow (Dataflow), and Apache Airflow (Airflow)
  • Collaborate with data scientists to implement machine learning models and workflows using libraries such as TensorFlow and scikit-learn
  • Utilize data manipulation libraries such as pandas, NumPy, and PySpark for data analysis and processing
  • Develop and maintain Python 3 (Python) applications and Application Programming Interfaces (APIs) to support data workflows and analytics
  • Monitor and troubleshoot data pipelines to ensure data quality and reliability
  • Participate in the deployment lifecycle of machine learning models and applications, including Machine Learning Operations (MLOps) and Large Language Model Operations (LLMOps) practices
  • Work with container orchestration tools such as Kubernetes (K8s) to manage and deploy applications in cloud environments
  • Stay updated with the latest trends and technologies in data engineering, DevOps, and cloud computing

You’ll likely have the following qualifications to succeed in this role:

  • Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field (or equivalent practical experience)
  • Familiarity with Big Data technologies (Hadoop, HDFS, BigQuery, EMR, Snowflake, Databricks)
  • Experience with data science tools (JupyterHub, MLflow, Vertex AI, Dataproc, Dataflow, Airflow)
  • Experience with data manipulation libraries (pandas, NumPy, PySpark)
  • Proficiency in Python, including experience in building APIs and applications
  • Familiarity with cloud platforms such as Google Cloud Platform (GCP), Amazon Web Services (AWS), and Microsoft Azure (Azure), and their services
  • Basic knowledge of Linux operating systems
  • Understanding of Kubernetes (K8s), MLOps/LLMOps, and experience with Large Language Models (LLMs) such as OpenAI, Claude, or Gemini (preferred)

In compliance with applicable laws, HSBC is committed to employing only those who are authorized to work in Canada. Applicants must be legally authorized to work in Canada as HSBC will not engage in immigration sponsorship for this position. 

As an HSBC employee, you will have access to tailored professional development opportunities to ensure you have the right skills for today and tomorrow. At HSBC, our overall goal is to provide a competitive Total Reward Package, with an appropriate mix of fixed pay, and variable pay, as part of an employee’s overall total compensation and benefits. Variable pay generally takes the form of discretionary, annual awards (sometimes referred to as a “bonus”). Additionally, HSBC offers a wide range of competitive and flexible benefits designed to help you improve your health and well-being, finances, and lifestyle.

All qualified applicants will receive consideration for employment without regard to age, ancestry, color, race, national origin, ethnicity, disability or medical condition, genetic information, military or veteran service, religion, creed, sex, gender, pregnancy, childbirth, caregiver status, marital status, citizenship or immigration status, sexual orientation, gender identity or expression or any other trait protected by applicable law. 

The final fixed pay offer will depend on the candidate and a number of variables, including but not limited to, role responsibilities, skill set, depth of experience and education, licensing/certification requirements, internal relativity, and specific work location.

At HSBC, our overall goal is to provide a competitive Total Reward Package, with an appropriate mix of fixed pay, and variable pay, as part of an employee’s overall total compensation and benefits. Variable pay generally takes the form of discretionary, annual awards (sometimes referred to as a “bonus”). Additionally, HSBC offers a wide range of competitive and flexible benefits designed to help you improve your health and well-being, finances, and lifestyle.