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Big Data Support Engineer Jobs in Ontario (NOW HIRING)

Cogency

Big Data Developer

Toronto, ON · Hybrid

... Engineer with strong expertise in Spark, Snowflake, AWS, Airflow, Big Data technologies, and ETL . ... Participate in Agile ceremonies, code reviews, testing, deployment, and production support.

New

TMX Group

Big Data Engineer

Toronto, ON · Hybrid

You are a self-directed professional, comfortable supporting the diverse data needs of multiple ... big data' technologies, with a focus on both bulk and streaming data. * Engineering Excellence:

Galent

Big data - Hadoop, Hive * Java * CI/CD tools and version control systems Additional Information 10+ ... Strong programming skills in Java. Proficient in writing complex SQL queries and working with ...

Rackspace Technology

Collaborate with enterprise architects, data architects, ETL developers & engineers, data ... supporting on-premise, cloud (Ideally AWS) and hybrid architectures to enable use cases in ...

ShyftLabs

Data Engineer

Toronto, ON · Hybrid

CA$100K - CA$140K/yr

The Opportunity ShyftLabs is seeking a skilled Data Engineer to support in designing, developing, and optimizing big data solutions using the Databricks Unified Analytics Platform. This role requires ...

TechBlocks

Data Engineer

Vaughan, ON

Role: GCP Data Engineer Location: Vaughan, ON Type: Full Time - Contract 6 months (Extendable ... The ideal candidate will have experience working with Python and big data technologies such as ...

ZoomInfo

Key Responsibilities: • Create and optimize big data extraction and processing pipelines • ... engineering and innovation skills. #J-18808-Ljbffr

Pelmorex

Data Engineer, DMP

Oakville, ON · Hybrid

You will work closely with data scientists, big data developers, and product managers, to create ... We may use artificial intelligence (AI) tools to support parts of the hiring process, such as ...

Pacer Group

Platform Engineer

Toronto, ON · Hybrid

Experience supporting production data platforms * Senior Platform Engineer with extensive experience in Big Data technologies, AWS Cloud, and data platform engineering * Strong expertise in designing ...

ZoomInfo

Build and optimize big data pipelines to extract and process signals from the web, job postings ... Collaborate closely with data scientists to support and integrate ML models into data workflows

KPMG

Data Support Senior Consultant

Toronto, ON

Support consultants will work as part of the CDST to assist clients facing teams with data ... Bachelors or Diploma in Computer Science, Database Management, Data Programming, Information ...

KPMG

Data Support Senior Consultant

Vaughan, ON

Support consultants will work as part of the CDST to assist clients facing teams with data ... Bachelors or Diploma in Computer Science, Database Management, Data Programming, Information ...

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All JobsBig Data Support Engineer JobsBig Data Support Engineer Jobs in Ontario

Big Data Support Engineer information

See Ontario salary details

$26K

$92.4K

$152.5K

How much do big data support engineer jobs pay per year?

As of Aug 28, 2026, the average yearly pay for big data support engineer in Ontario is $92,417.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,000.00 and $119,500.00 per year, depending on experience, location, and employer.

What is a big data support engineer?

A Big Data Support Engineer is an IT professional responsible for maintaining, troubleshooting, and optimizing big data systems and platforms. They help ensure that data pipelines, storage solutions, and analytics tools run smoothly and efficiently, often working with technologies like Hadoop, Spark, and cloud-based data services. Their role involves resolving technical issues, monitoring system performance, managing data security, and collaborating with data engineers and analysts to support business operations. These engineers also document processes and provide technical support to users leveraging big data platforms. Overall, they play a crucial role in enabling organizations to manage and utilize large volumes of data effectively.

How does a big data support engineer typically interact with development and operations teams to resolve issues?

A Big Data Support Engineer regularly collaborates with both development and operations teams to troubleshoot and resolve data pipeline, cluster, or performance issues. They often serve as a bridge, translating operational alerts and technical problems into actionable insights for developers, while also ensuring that solutions adhere to infrastructure and security best practices. This cross-functional teamwork often involves participating in incident response meetings, root cause analyses, and implementing long-term fixes, making strong communication and problem-solving skills essential for success in this role.

What are the key skills and qualifications needed to thrive as a big data support engineer, and why are they important?

To thrive as a Big Data Support Engineer, you need expertise in data analysis, database management, troubleshooting, and strong knowledge of big data frameworks, usually backed by a degree in computer science or a related field. Familiarity with Hadoop, Spark, SQL, cloud platforms, and relevant certifications (like Cloudera or AWS) is typically required. Excellent problem-solving abilities, communication skills, and the capacity to work under pressure help you excel in supporting complex big data environments. These skills ensure efficient resolution of technical issues, minimize downtime, and maintain the performance and reliability of critical data systems.

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

AspectBig Data Support EngineerData Engineer
Primary FocusMaintaining and troubleshooting big data systems and infrastructureDesigning, building, and optimizing data pipelines and architectures
Skills & CertificationsKnowledge of Hadoop, Spark, Linux, scripting; certifications like Cloudera or HortonworksProficiency in SQL, Python, ETL tools; certifications in cloud platforms or data engineering
Work EnvironmentSupport teams, data centers, cloud environmentsDevelopment teams, data warehouses, cloud platforms

While both roles work with big data technologies, a Big Data Support Engineer primarily focuses on maintaining and troubleshooting existing systems, whereas a Data Engineer designs and builds data pipelines and architectures. The roles often overlap but differ in their core responsibilities and skill sets.

What are popular job titles related to Big Data Support Engineer jobs in Ontario?

For Big Data Support Engineer jobs in Ontario, the most frequently searched job titles are:

What job categories do people searching Big Data Support Engineer jobs in Ontario look for?

The top searched job categories for Big Data Support Engineer jobs in Ontario are:

Big Data Support Engineer jobs near you
Infographic showing various Big Data Support Engineer job openings in Ontario as of August 2026, with employment types broken down into 1% As Needed, 67% Full Time, 28% Part Time, and 4% Contract. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $92,417 per year, or $44.4 per hour.

Big Data Developer

Cogency

Toronto, ON • Hybrid

Full-time

Posted yesterday

New

Job description

Job Title: Big Data Developer – Spark, AWS, Airflow & Snowflake


Company: Cogency Inc.


Location: Greater Toronto Area, ON


Work Model: Hybrid – 4 Days Onsite


Job Type: Full-Time


Job Summary


Cogency Inc. is seeking a skilled Big Data Developer / Data Engineer with strong expertise in Spark, Snowflake, AWS, Airflow, Big Data technologies, and ETL. The successful candidate will design, develop, and optimize scalable data pipelines and ETL processes while ensuring data quality, security, reliability, and performance.

The role involves working closely with cross-functional teams in an Agile environment to deliver robust data solutions supporting analytics, reporting, and business intelligence initiatives.


Key Responsibilities


  • Design, develop, and maintain scalable data ingestion pipelines and ETL workflows.
  • Build and optimize data pipelines, transformation frameworks, and processing workflows.
  • Develop and optimize Apache Spark applications for large-scale data processing.
  • Work with Hadoop, Spark, and Hive within Big Data environments.
  • Design and optimize Snowflake data solutions, data models, and SQL workloads.
  • Develop complex SQL queries, stored procedures, transformations, and data models.
  • Integrate Snowflake with enterprise data sources and BI/reporting platforms.
  • Develop ETL workflows using Informatica, Talend, Apache Airflow, or similar technologies.
  • Build and manage workflow orchestration using Apache Airflow.
  • Develop data solutions on AWS, leveraging services such as S3, Glue, and Lambda.
  • Monitor, troubleshoot, and resolve data pipeline and platform performance issues.
  • Implement data quality, integrity, security, and governance controls.
  • Develop APIs and data integrations using Scala or Java.
  • Implement CI/CD, DevSecOps, and Infrastructure-as-Code practices.
  • Maintain technical documentation for data pipelines, transformations, and data models.
  • Collaborate with Data Architects, Developers, DevOps teams, Business Analysts, and other stakeholders.
  • Participate in Agile ceremonies, code reviews, testing, deployment, and production support.
  • Leverage GenAI and AI-assisted development tools to improve developer productivity and code quality.


Required Skills & Experience


  • 5+ years of experience in Data Engineering, Big Data, or ETL development.
  • Strong hands-on experience with:
  • Apache Spark
  • Hadoop
  • Hive
  • Snowflake
  • Strong SQL and data modeling skills.
  • Programming experience in Scala or Java.
  • Experience developing APIs and enterprise data integrations.
  • Experience with ETL technologies such as Informatica, Talend, or Apache Airflow.
  • Strong understanding of data ingestion, transformation, processing, and pipeline optimization.
  • Experience working with cloud platforms, preferably AWS.
  • Understanding of CI/CD, DevSecOps, and Infrastructure-as-Code practices.
  • Experience working in Agile delivery environments.
  • Strong troubleshooting, analytical, and problem-solving skills.
  • Excellent communication and collaboration skills.


Preferred / Nice-to-Have


  • Hands-on experience with AWS Glue, S3, Lambda, and other AWS data services.
  • Strong experience with Apache Airflow or similar orchestration platforms.
  • Experience with GitHub Actions, Git, and automated testing.
  • Knowledge of Python or other scripting languages.
  • Experience with Shell/Bash scripting.
  • Exposure to Docker, Kubernetes, or OpenShift.
  • Experience with Infrastructure-as-Code tools such as Terraform.
  • Experience with GenAI tools for code generation, code review, and developer productivity.


Education


  • Bachelor's or Master's degree in Computer Science, Data Engineering, Information Technology, or a related discipline.


Key Competencies


  • Big Data Engineering
  • Apache Spark
  • Snowflake
  • AWS Cloud
  • ETL/ELT Development
  • Data Pipeline Engineering
  • Apache Airflow
  • SQL & Data Modeling
  • Scala / Java
  • API Integration
  • DevSecOps & CI/CD
  • Data Quality & Governance
  • Agile Delivery
  • Problem Solving & Troubleshooting


Work Model: Greater Toronto Area – 4 Days Onsite per Week

Employment Type: Full-Time

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