Data Engineering Practice Lead

2 weeks ago

Ottawa, Ontario, Canada CB Canada Full time
Job Description:

The Senior Data Engineer Service Provider will be responsible for leading the delivery of data on data and analytics platform. These services are at the forefront of building out data engineering practice cloud-native technologies. The Senior Data Engineer Service Provider must have experience in leading, designing, implementing, and collaborating with stakeholders to achieve the best results for our clients.

Key Responsibilities:
  • Design and Implementation: Proven design, build and implementation of batch and real-time data pipelines. Driven by automated repeatable delivery of data that aligns to enterprise data governance standards.
  • Data Modeling: Experience in developing and proposing data models that conform to requirements. Responsible to ensure the proposed design, optimally addresses access and query patterns; data consumption and adheres to internal architecture standards.
  • Collaboration: Experienced collaboration working with various stakeholders across the business, data scientists and IT. Working closely building relationships, refining data requirements to meet various data and analytics initiatives and data consumption requirements
Requirements:
  • Speed and Quality: Increase the overall speed in which data is onboarded to the Data and Analytics platform. Building robust data pipelines to enable larger data consumption on the Data and Analytics Platform
  • DevSecOps: Increase the overall quality of data pipeline development through DevSecOps
  • Programming Experience: Programming experience in Spark using modern languages such as Scala
  • Modern Data Architectures: Experience working with modern data architectures like Azure Data Lake Storage, Azure Databricks, Azure Synapse (formerly SQL Data Warehouse) and Delta Lakes
  • Data Engineering Principles: Experience leading Data Engineering principles within an organization/team.
  • Database Modeling Techniques: Knowledge and expertise of database modeling techniques: Data Vaults, Star, Snowflake, 3NF, etc.
  • Streaming Data Architecture: Experience working with streaming data architecture and technologies for real-time: Spark Streaming, Kafka, Flink, Storm
  • Database Technologies: Experience working with relational and non-relational database technologies: SQL Server, Oracle, Cassandra, MongoDB, CosmosDB, HBase
  • Source Code and Configuration Management: Experience working with source code and configuration management environments such as Azure DevOps, Git, Maven, Nexus
Assets:
  • Azure Experience: Experience within Azure environment
  • Scala and Spark Experience: Strong Scala and Spark experience
  • Data Platform Modernization: Experience modernizing data platforms.
  • Data Vault Experience: 2 to 3 projects developing Data Vault

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