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Insight Global
Data EngineerInsight Global • Vancouver, BC, CA
Data Engineer

Data Engineer

Insight Global • Vancouver, BC, CA
10 hours ago
Job type
  • Full-time
Job description
Required Skills & Experience 5+ years of experience as a Data Engineer Experience with Azure Data Factory, Azure Databricks, Snowflake, and Storage Accounts Experience with Python, specifically PySpark for developing and optimizing pipeline builds Experience with DBT/DLT and working with Medallion Architecture Experience with CI/CD principles and best practices, including Azure DevOps and Repos Experience with Azure Cloud deployments and configurations Experience with bug tracking and task management software such as JIRA Experience managing outages, customer escalations, crisis management, and similar circumstances Nice to Have Skills & Experience Azure certification Experience with Terraform and ARM templates Retail and/or e-commerce experience; experience working for a multi-channel retailer Experience with Snowflake or any enterprise data warehouse Job Description Insight Global is looking to hire a Sr. Data Engineer for a retail client based in Vancouver. This role is a hybrid position and requires 3 days onsite per week in Downtown Vancouver. You will be joining a team that works heavily with customer data—owning the customer data pipelines that gather data coming from multiple sources and consolidating that data for different use cases. Some use cases include segmentation, data and analytics, advanced analytics for ML models to generate product recommendations, etc. You will have a strong knowledge of the Azure infrastructure and can build Azure pipelines. You will make general recommendations to the client on how to improve the current infrastructure. This role is not tied to a certain body of work; rather, you will support multiple workstreams and work with the Product teams to prioritize. Other duties and responsibilities include: Data pipeline creation and maintenance Stack: GCP, Azure Cloud, Azure Databricks, Snowflake Includes engineering documentation, knowledge transfer to other engineers, future enhancements, and maintenance Create secure data views and publish them to the Enterprise Data Exchange via Snowflake for other teams to consume Data pipeline modernization and migration via Databricks Delta Live Tables (DLT) and Unity Catalog Leverage existing CI/CD processes for pipeline deployment Adhere to PII encryption and masking standards Orchestration tools: ADF, Airflow, Fivetran Languages: SQL, Python Data Modeling: Star and Snowflake schemas Streaming: Kafka, Event Hubs, Spark, Snowflake Streaming DevOps Support: Support improvements for current CI/CD processes Production monitoring and failure support
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Data Engineer • Vancouver, BC, CA

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