What are the responsibilities and job description for the Lead Azure Data Engineer position at TechVest Global?
Job Details
Job Description
Job Description
Role: Lead Azure Data Engineer
Location: Montreal (or) Toronto, Canada
Relevant:
5 years of experience in pipeline design and development (Batch and Streaming) using Azure/snowflake cloud services, primarily on Azure Datalake Gen2, Azure Data Factory, Azure Event Hub, Databricks, and Snowflake.
Must Skills:
Databricks, Snowflake, Pyspark, SQL, Data Modeling
Responsibilities:
Excellent communication, work closely with Customer
Expertise in above skills
Complete the user stories in the assigned sprint, highlight the risks at right time
JD:
Collaborate with stakeholders to understand requirements, data solutions, data models and mapping documents.
Lead the design, development, and implementation of data solutions using Azure Data Lake Storage (ADLS), Azure Data Factory, Event Hub, Databricks, and Snowflake.
Oversee the end-to-end data pipeline, ensuring data quality, integrity, and security.
Lead the deployment activities including the Dev test approval, PR approval, Collaboration with DevOps team, Release mgmt. for deployment into all environments including production and provide knowledge sharing to Data operations team
Assist data analysts with technical input.
Provide data engineering inputs to the data solution architect.
Lead the effort estimates/story point estimates for the sprint.
Mentor and guide a team of data engineers.
Foster a collaborative environment to encourage knowledge sharing and continuous improvement.
Conduct code reviews and ensure adherence to coding standards and best practices.
Location: Montreal (or) Toronto, Canada
Relevant:
5 years of experience in pipeline design and development (Batch and Streaming) using Azure/snowflake cloud services, primarily on Azure Datalake Gen2, Azure Data Factory, Azure Event Hub, Databricks, and Snowflake.
Must Skills:
Databricks, Snowflake, Pyspark, SQL, Data Modeling
Responsibilities:
Excellent communication, work closely with Customer
Expertise in above skills
Complete the user stories in the assigned sprint, highlight the risks at right time
JD:
Collaborate with stakeholders to understand requirements, data solutions, data models and mapping documents.
Lead the design, development, and implementation of data solutions using Azure Data Lake Storage (ADLS), Azure Data Factory, Event Hub, Databricks, and Snowflake.
Oversee the end-to-end data pipeline, ensuring data quality, integrity, and security.
Lead the deployment activities including the Dev test approval, PR approval, Collaboration with DevOps team, Release mgmt. for deployment into all environments including production and provide knowledge sharing to Data operations team
Assist data analysts with technical input.
Provide data engineering inputs to the data solution architect.
Lead the effort estimates/story point estimates for the sprint.
Mentor and guide a team of data engineers.
Foster a collaborative environment to encourage knowledge sharing and continuous improvement.
Conduct code reviews and ensure adherence to coding standards and best practices.
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