Data Engineer

Successful Data Engineer candidate will have:

• Degree or Diploma in Computer Science / Engineering, Data Sciences or other quantitative

  discipline;

• 5+ years’ experience in ETL, data design, data architecture, data management and data modelling;

• Expert proficiency with SQL Server and SSIS is required;

• Create and maintain data pipelines and ETL processes;

• Experience with Python, big data tools and cloud services considered an asset;

• Be responsible for monitoring and addressing database issues and problems and ensuring they are

  in line with company policies and any external regulations that may apply;

• Provide insight into the changing database integration, storage and utilization requirements for the

  company and offer suggestions for solutions;

• Oversee the integration of data from legacy and on-premises systems to new solutions;

• Working knowledge of data management as laid out by Data Management Association (DAMA) and

  the Data Management Body of Knowledge (DMBoK);

• Ability to communicate technical information effectively in an easy to understand language;

• Educate staff members through training and individual support;

• Knowledge and exposure to data privacy and confidentiality regulations such as Personal

• Information Protection and Electronic Documents Act (PIPEDA);

Typical activities in the Data Engineer role include:

• Work closely with the Enterprise Analytics team to create and maintain ELT processes;

• Assemble large, complex datasets that meet functional / non-functional business requirements;

• Consulting Business leaders on data and information management practices and

  governance;

• Identify, design, and implement internal process improvements: automating manual processes,

  optimizing data delivery, re-designing infrastructure for greater scalability, etc.;

• Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and other technologies;

• Work with stakeholders including the Executive, to assist with data-related technical issues and

  support their data infrastructure needs.

• Create data tools for analytics and data scientist team members that assist them in building and

  optimizing our business.

• Work with data and analytics experts to strive for greater functionality in our data systems.

• Championing efforts to improve business performance through enterprise information capabilities,

  such as master data management (MDM), metadata management, analytics, content management,

  data integration, and related data management or data infrastructure;

• Provide insight into the changing database integration, storage and utilization requirements for the

  company and offer suggestions for solutions;

• Monitor and understand Information Management trends and emerging technologies.