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Description du poste

Are you a Data Engineer guru? Do you have strong managerial and leadership skills? If so, we want to meet you!

This position manages a Data Engineering team and has primary responsibility of building and maintaining an Analytics Platform with high quality, clean data that can be used to power the analytics team and other verticals to make informed decisions with data. This position is responsible for defining best practices around enterprise class data platforms and developing core data engineering capabilities including, but not limited to, data quality processes, data pipelines, data aging and change management systems as well as containerization and model automation. The role manages a team of Data engineers responsible for building solutions which are flexible, performant and scalable. Incumbents must have in-depth knowledge of analytic platforms.

Our client has been around for over 15 years and has remained a well reputed company in Canada.

Position Responsibility:

  • Manages a team of Data Engineers and is responsible for the delivery of a next gen Data Platform
  • Work Closely with existing IT team across the company to develop optimal data pipelines for ingesting data from various sources.
  • Identify and work with data scientist and analysts to understand their daily workloads and suggest techniques and tools for optimization.
  • Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using AWS tools like glue, step functions, lambda and others.
  • Develop relationships with IT config, security and other teams across the company to understand and develop data science development lifecycle.
  • Develop code in python to write serverless functions to automate the data flow as per existing architecture.
  • Develop code in python for data quality for pipelines to reduce time spent on data cleaning.
  • Being able to initiate and coordinate discussion with vendors and engage the required participants leading to delivery.
  • Develop integration patterns with third party and internal systems of data like salesforce, mobile and others.
  • Develop partnerships with data, IT security, Cloud infrastructure and other teams at the company to ensure timely execution of responsibilities for data science projects.
  • Responsible for timely execution of data engineering projects in fast paced environment with a team of data engineers.
  • Develop change management and data quality processes to ensure users of data are able to focus on insights.
  • Strong understanding of basic data science principles.

Qualifications:

  • Minimum of a Bachelor’s degree in Computer Science, engineering or related degree and seven (7) years of relevant experience including management or leadership experience or an equivalent combination of education, training and experience.
  • Strong leadership skills to move the organization through change and drive to succeed and identify and solve potential obstacles.
  • Advanced working knowledge of ETL processes and databases including but not limited to redshift.
  • Working knowledge of serverless ecosystem on AWS and its advantages and disadvantages.
  • Good understanding of IT security processes around data.
  • Experience with data pipeline and workflow management tools like AWS Step functions, Airflow.
  • Experience integrating and maintaining data bricks or like solutions.
  • Pushing machine learning models to and from mobile application.
  • Experience with AWS cloud services: Redshift, Lambda, Glue (ETL tooling).
  • Experience with data optimization and compression techniques like parquet, Avro, gzip, snappy.
  • Strong project management and organizational skills.
  • Experience with big data tools: Spark, Hadoop, etc.
  • Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.

Information du contact

Don't miss out on this great opportunity! Apply Today!

Qualified candidates please submit resume to [email protected] and on my cellphone 416-768-9925