Data Science Software Engineer Jobs in Manitoba

Minimum 2 years of related experience.

Coachable, fast learner who can pick up new skills and processes quickly

Analytical mindset with a skillset focused on extracting & analyzing data

Knowledge of programming languages SQL, PowerQuery M, R, or Python

Knowledge of Microsoft Power Platform Power BI/Automate/Apps

Support the Data Team with deep ad-hoc analysis that will drive performance and keep Sales and Customer teams accountable

Knowledge of data management fundamentals and data storage principles

3+ years of non-internship professional software development experience

2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience

Experience programming with at least one software programming language

Experience using big data technologies (Spark, EMR, Presto, etc.)

Knowledge of distributed systems as it pertains to data storage and computing

Experience working with product owners to understand and implement business requirements

2+ years of programming experience, ideally in a compiled language (C#, Java, Go, etc.).

Experience developing and extending systems of moderate complexity

Practical experience writing Map/Reduce, Spark or Hive/Presto or using a machine learning frameworks

Experience working well in a very fast-paced and continuously changing environment

Create high quality, maintainable code that processes and analyzes almost 400 million events daily (and doubling every year)

Delve deep into the user experience side to envision the next generation architecture of the tool suite

Use your experience to help define and apply best practices for a broad platform of technologies in a cloud-based environment

Partner with the Engineering Manager and other Tech Leads to recruit and build the team

5+ years of experience working as a professional developer in cloud and data.

Experience with full-stack development (we currently use Django, React, and Postgres)

Experience with data processing engines (we use Beam and Big Query)

Have a strong background in developing distributed systems with experience in scalable data pipelines

Experience with RESTful APIs and server-side APIs integration

Experience with CI/CD pipeline orchestration, leveraging Gitlab, Helm, and Terraform

Experience with administration of Docker or Kubernetes infrastructure

Appreciate the importance of excellent documentation and data debugging skills.

Excel at taking vague requirements and crystallizing them into scalable data solutions

Work with a first version of requirements provided by the PM

Experience designing data workflows from scratch

Strong experience in data modelling and schema design, with relational or non relational databases

Experience integrating and configuring large volume datastores such as vector or graph databases(Pinecone, Milvus, Neo4J etc)

Experience Scaling data processing pipelines for multi tenancy use cases

Experience working with real time data systems with technologies such as Kafka, Flink, Pubsub, etc

Prior experience with writing and debugging data pipelines using a distributed data framework (Spark / Hadoop / Pig etc)

Knowledge of a scientific computing language (such as Scala or Python) and SQL

Experience with full stack development languages such as Java or Go, and front-end frameworks such as React

The ability to communicate cross-functionally, derive requirements and architect shared datasets

Design, develop, and own data pipelines, models, and products that power Stripe’s Growth, Sales, and Marketing teams

Our stack spans tools in Spark, Scala, Python, Spark, SQL, Presto, Airflow, AWS, Java, Go, and React