Software Engineer, Data Platform
Canada; must reside in British Columbia or OntarioFull-TimeMiddle
Salary90,000 - 120,000 CAD per year
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Job Details
- Experience
- Minimum of 2 years
- Required Skills
- AWSPythonSQLSnowflakeTypeScriptSparkBigQuerydbtRedshiftDatabricks
Requirements
- Minimum of 2 years of experience in software engineering, data engineering, or analytics engineering roles.
- Experience contributing to centralized data platforms or large-scale data infrastructure initiatives.
- Strong proficiency in SQL and at least one general-purpose programming language such as Python or TypeScript.
- Familiarity with modern data warehouse or lakehouse platforms such as Snowflake, Redshift, BigQuery, or Databricks.
- Experience working with AWS services or equivalent cloud technologies.
- Understanding of scalable data pipeline design and distributed data processing concepts.
- Familiarity with tools and frameworks such as dbt, Spark, Kafka Streams, or Flink is considered an asset.
- Strong analytical thinking, problem-solving skills, and curiosity.
- Excellent collaboration and communication skills within cross-functional and remote teams.
- Ability to work independently while contributing to a highly iterative and collaborative engineering culture.
Responsibilities
- Design, build, and maintain scalable data infrastructure and centralized platform capabilities using modern cloud technologies.
- Develop robust batch and streaming data pipelines that ingest, process, and serve data across multiple teams and applications.
- Contribute to the implementation of a modern data lakehouse architecture supporting scalable storage, analytics, and secure data access.
- Create reusable SDKs, libraries, and internal tooling that simplify how teams interact with the data platform.
- Establish and promote best practices related to data governance, data quality, security, and compliance.
- Collaborate with Engineering, Product, and business stakeholders to identify data requirements and deliver scalable solutions aligned with organizational goals.
- Optimize platform performance, reliability, and maintainability while supporting evolving data and analytics needs.
- Participate in continuous improvement initiatives focused on modernizing infrastructure, tooling, and development practices.
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