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Entry Level Streaming Data Engineer Jobs in Montreal, QC

... Engineer (DevOps) to join our TecsysIQ Data & AI team. This is a hybrid role that builds and ... Develop and operate real-time streaming and change data capture (CDC) pipelines across the ...

About You We're hiring a Senior Data Engineer for Data Insights in Montreal-someone with a Data as ... Migrate legacy ETL processes to modern, efficient streaming and incremental pipelines, choosing ...

Knowledge of Message Queue Systems, especially Apache Kafka and Kafka Streams. * AWS serverless ... If you would like more information about how your data is processed, please contact us. apply for ...

... streaming, and bring to life through our global theme park destinations, consumer products, and ... You will be part of a team of GIS developers responsible for sourcing geospatial data in many ...

ABOUT YOU We are looking for a Full-Stack Engineer who is curious, detail-oriented, and ... equivalent streaming platforms. * Familiarity with Redis or other in-memory data stores.

Full-Stack Software Engineer

Montreal, QC · On-site +1

CA$120K - CA$150K/yr

Experience with relational data modeling and SQL (Postgres preferred). You know what an index does ... Experience with queues and async fan-out (SQS, RabbitMQ, Kafka, Redis Streams). * Working knowledge ...

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Entry Level Streaming Data Engineer information

What is the difference between Entry Level Streaming Data Engineer vs Data Analyst?

AspectEntry Level Streaming Data EngineerData Analyst
Required SkillsKnowledge of streaming platforms (e.g., Kafka, Spark), basic programming, data modelingData visualization, SQL, statistical analysis, Excel
CertificationsOptional certifications in data engineering or cloud platformsCertifications in data analysis or business intelligence tools
Work EnvironmentDeveloping real-time data pipelines, working with streaming data systemsInterpreting data, creating reports, supporting decision-making
Industry UsageTech, finance, e-commerce, where real-time data processing is criticalMarketing, finance, healthcare, focusing on data insights

In summary, Entry Level Streaming Data Engineers focus on building and maintaining real-time data pipelines using streaming technologies, while Data Analysts interpret and visualize data to support business decisions. Both roles require different skill sets but are essential in data-driven industries.

Can I get an entry level streaming data engineer job with no experience?

Entry level streaming data engineer roles typically require some knowledge of data processing tools like Apache Kafka or Spark, and familiarity with programming languages such as Python or Java. While prior experience is often preferred, candidates with relevant internships, certifications, or strong foundational skills in data concepts can sometimes qualify for entry-level positions. Demonstrating a willingness to learn and understanding of streaming architectures can improve chances of securing such roles.

What is an entry level streaming data engineer?

An entry level streaming data engineer is a professional responsible for designing, building, and maintaining systems that process real-time data streams. They typically work with tools like Apache Kafka, Spark Streaming, or Flink and require foundational knowledge of programming, data architecture, and cloud platforms. This role often involves collaborating with data scientists and software engineers to ensure efficient data flow and availability.

What are the most commonly searched types of Streaming Data Engineer jobs in Montreal, QC?

The most popular types of Streaming Data Engineer jobs in Montreal, QC are:

What are popular job titles related to Entry Level Streaming Data Engineer jobs in Montreal, QC?

For Entry Level Streaming Data Engineer jobs in Montreal, QC, the most frequently searched job titles are:

What job categories do people searching Entry Level Streaming Data Engineer jobs in Montreal, QC look for?

The top searched job categories for Entry Level Streaming Data Engineer jobs in Montreal, QC are:

Infographic showing various Entry Level Streaming Data Engineer job openings in Montreal, QC as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 10% Part Time, 3% Contract, and 10% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Data Engineer (DevOps)

Tecsys Inc.

Montreal, QC • On-site, Remote

Full-time

Posted 22 days ago


Job description

Having recognized the advantages of remote work, including employee morale, productivity, reduced commuting on employee wellbeing and the environment, we are proud to be a digital-first company. The technologies and programs in which we invested have provided a fantastic foundation to this end. Our digital-first work environment, together with our conveniently located offices and collaborative workspaces, provide our team with the freedom and flexibility to work in the way that makes our employees most productive.

About us

Tecsys is a fast-growing innovator offering supply chain solutions to industry leading healthcare systems, hospitals, and pharmacy businesses to distributors, retailers, and 3PLs. We work with industry leaders to transform their supply chains through technology. If you thrive on tackling interesting challenges with continuous learning opportunities, then Tescys could be a good fit for you!

We're looking for a Data Platform Engineer (DevOps) to join our TecsysIQ Data & AI team. This is a hybrid role that builds and operates the cloud data platform powering our analytics and AI products on Databricks and AWS.

You will own the infrastructure-as-code and delivery pipelines that provision and deploy the platform, and the Databricks jobs and streaming pipelines that move and shape data through it. You'll partner closely with Data Platform Developers, application dev teams, and Product Owners - standing up new customer environments, evolving the CI/CD and release process, and creating and maintaining the data pipelines that keep the platform running reliably at scale. If you are equally comfortable writing Terraform and debugging a Spark Structured Streaming job, this role is for you.

ResponsibilitiesPlatform & DevOps
  • Provision and evolve AWS and Databricks accounts and workspaces using Terraform across multiple regions and environments, managing remote state and per-environment configuration.
  • Own the Helm charts and Kubernetes Jobs that onboard new customer environments and deploy the application layer onto provisioned workspaces.
  • Build and maintain Docker images and the Java/Maven build pipeline, publishing artifacts to internal artifact and container registries.
  • Integrate build, test, and deployment into CI/CD pipelines, and improve release management and versioning across interdependent repositories.
  • Manage secrets and credentials safely through cloud secret management and Kubernetes - never in source control.
Data Platform & Pipelines
  • Design, build, and maintain Databricks jobs and pipelines - including data curation, transformation, and initial bulk-load workflows.
  • Develop and operate real-time streaming and change data capture (CDC) pipelines across the ingestion and transformation layers using Spark Structured Streaming.
  • Build and evolve end-to-end data movement across the Bronze, Silver, and Gold data layers, extending pipelines to handle new sources and schema changes as the platform grows.
  • Develop and maintain reusable pipeline components and frameworks so new data workflows can be onboarded and shipped quickly.
  • Tune clusters and SQL warehouses for cost and performance, and manage catalog, schema, and access governance across environments.
  • Collaborate with Data Platform Developers, Product Owners, and business stakeholders in an Agile environment to deliver high-quality data products.

Requirements

Qualifications
  • Hands-on experience with Databricks and Apache Spark, including building batch or streaming data pipelines (mandatory).
  • Strong Terraform skills and comfort managing cloud infrastructure on AWS.
  • Working knowledge of Kubernetes and Helm, and containerization with Docker.
  • Proficiency in Python (PySpark) and/or Java, plus strong SQL for data validation and troubleshooting.
  • Experience with Git-based workflows and CI/CD pipelines in a multi-repository codebase.
  • Understanding of data quality, ETL/ELT, and data observability concepts.
  • Experience working in Agile teams alongside Data Platform Developers and Product Owners.
  • Strong analytical, problem-solving, and communication skills.

We understand that experience comes in many forms and that careers are not always linear. If you don't meet every requirement in this posting, we still encourage you to apply.

At Tecsys, we are committed to fostering a diverse and inclusive workplace where all employees feel valued, respected, and empowered. We believe that diversity drives innovation and strengthens our ability to deliver exceptional solutions. We welcome and encourage applicants from all backgrounds, experiences, and perspectives to join our team.

Tecsys is an equal opportunity employer. Accommodation is available for applicants selected for an interview.

NB: if you are applying to this position, you must be a Canadian Citizen or a Permanent Resident of Canada, OR, have a valid Canadian work permit.