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Company Overview

Stream Systems () is a leading-edge technology company that enables enterprises to optimize and make better decisions. Our Sim Opti intelligence platform brings AI, machine learning and simulation to power business intelligence across complex operations, in any industry.

Reporting to the Software Development Manager, we are looking for a Data Developer experienced in continuous data process improvement across a range of data systems and subsystems. For this role, you will work closely with our data producers and consumers to enable Stream to automate data provisioning across data domains for multiple data use cases. Your data engineering expertise will implement data architectures, most importantly data mesh.

Your ability to implement data technologies quickly and efficiently for any data layer is critical to our agile data flow.

The role’s direct responsibilities include:

• Implement data ingestion and data integration solutions to support Stream’s simulation platform on AWS as part of a data mesh strategy.
• Manage and build ETL processes, extraction & integration of data from various data sources enabling a continuous data value stream.
• Oversee data quality monitoring, including processing, management and cleaning of data flows leveraged for analytics purposes while ensuring federated governance.
• Create custom data models for automated analysis, training machine learning, and enabling embedded BI reporting with row level security.
• Leverage best practices and best-in-class products and services to build cost-effective, scalable, and reliable data pipelines, data domains and data consumer API’s.
• Define and manage relational and distributed semi-structured No
  
  SQL data warehouses and schemas that form the core of data mesh or fabric architectures.
• Translate data requirements into detailed designs and pipeline architecture, ensuring proper documentation of methodologies including deployable data services with a data mesh.
• Define best practices around data lineage, versioning, services deployment, extraction, modeling, consumption & governance at Stream.

To ensure success in the role, you will need the following:

• Experience and formal qualifications in a STEM related discipline, such as Engineering or Computer Science, or certification and extensive work experience in a data centric development role with an understanding of how to implement data system architectures (distributed data mesh preferred)
• Experience designing and implementing data pipeline solutions accessing data from big data frameworks (AWS, GCP Big Query) as well as hybrid architectures with on-premise data connectors (SQL Server, Postgre
  
  SQL, Historian, Time series)
• Data stack working proficiency in SQL, Python, Java, and API development utilizing Graph
  
  QL.
  
  Experience with messaging platforms like Kafka or Rabbit
  
  MQ, data ingestion tools such as Airbyte, DBT, Databricks, MLflow an asset.
• Experience in data analytics engineering, orchestrating data pipelines, performance tuning, and script and test automation development.
• Experience architecting ETL solutions for a wide variety of sources, data abstractions, and data pipelines for real-time, streaming, batch, and on-demand workloads.
• Experience with data security strategies, configuring security for reporting, and certifications such as SOC 2.

This is a full-time position based on a 40-hour work week. We are driven by objectives, however, not timesheets. Stream’s head office is location in Calgary, Alberta with remote workers located across the country in British Columbia, Ontario, and Quebec. We are happy to provide a hybrid work environment, enabling you to work remotely as needed. We encourage a strong collaborative culture and provide work spaces in office for team collaboration, design, planning sessions and social activities.

Company benefits are available to our full-time, permanent employees and include extended health care, dental, long-term disability, AD&D, and life insurance for you and your dependents. The real benefits, in our opinion exist in the ability to become part of a flexible, passionate, and dedicated team where we continue to learn from one another every day. If you love that small-company feel with big-company goals, Stream just might be a fit for you.

Come do great things with us!