At Arterra Wines Canada, we love inspiring the big and small moments that happen when our products are shared and enjoyed. For us it’s not just about what’s in and on the bottle, it’s what happens in people’s lives when we’re a part of them that keeps us thirsting for more and not resting on our laurels as Canada’s largest and most enjoyed wine company. We put the consumer at the center of everything we do and we’re looking for people who do the same.

The Data Engineer plays a lead role in the Data Science team building and operationalizing the data necessary for the enterprise data science initiatives following industry standard practices and tools. The bulk of the data engineer’s work would be in building, managing and optimizing data pipelines and then moving these data pipelines effectively into production for data scientists, or any role that needs curated data for data and analytics use cases across the enterprise.

The data engineer will be the key interface in operationalizing data and analytics on behalf of the business unit(s) and organizational outcomes. This role will require a creative and collaborative working relationship with IT and the wider business. It will involve evangelizing effective data management practices and promoting better understanding of data and analytics. The data engineer will also be tasked with working with key business stakeholders, IT experts and subject-matter experts to plan and deliver optimal analytics and data science solutions.

Additionally, data engineers will also be expected to collaborate with data scientists, data analysts and other data consumers and work on the models and algorithms developed by them in order to optimize them for data quality, security and governance and put them into production.

What you will be doing:

• Build data pipelines: The primary responsibility of the data engineer will be to work with data scientists and business users to design, create and maintain data pipelines that serve data required for ML solutions, and deliver the output to downstream systems and users.
• Drive Automation: The data engineer will be responsible for using innovative and modern tools, techniques and architectures to partially or completely automate the most-common, repeatable and tedious data preparation and integration tasks in order to minimize manual and error-prone processes and improve productivity.
• Educate and train: The data engineer should be curious and knowledgeable about new data initiatives and how to address them. This includes applying their data and/or domain understanding in addressing new data requirements. They will also be responsible for proposing appropriate (and innovative) data ingestion, preparation, integration and operationalization techniques in optimally addressing these data requirements. The data engineer will be required to train counterparts - such as data scientists, data analysts, LOB users or any data consumers - in these data pipelining and preparation techniques, which make it easier for them to integrate and consume the data they need for their own use cases.
• Collaborate across departments: The data engineer will need strong collaboration skills in order to work with varied stakeholders within the organization. In particular, the data engineer will work in close relationship with data science teams and with business (data) analysts in refining their data requirements for various data and analytics initiatives and their data consumption requirements.
• Be a data and analytics evangelist: The data engineer will be considered a blend of data and analytics “evangelist,” “data guru” and “fixer.” This role will promote the available data and analytics capabilities and expertise to business unit leaders and educate them in leveraging these capabilities in achieving their business goals.

What you will bring:

• Completion of a degree in data science, statistics, computer science, or a related quantitative discipline - or a combination of education, training and experience deemed equivalent
• 6-8 years in data management disciplines including data integration, modeling, optimization and data quality, and/or other areas directly relevant to data engineering responsibilities and tasks
• 3-5 years experience working in cross-functional teams and collaborating with business stakeholders in support of a departmental and/or multi-departmental data management and analytics initiative
• 6-8 years in data management disciplines including data integration, modeling, optimization and data quality, and/or other areas directly relevant to data engineering responsibilities and tasks
• 3-5 years experience working in cross-functional teams and collaborating with business stakeholders in support of a departmental and/or multi-departmental data management and analytics initiative
• Strong experience with advanced analytics tools for Object-oriented/object function scripting using languages such as R, Python, Java, C++, Scala, and others
• Strong experience in working with data science teams in refining and optimizing data science and machine learning models and algorithms
• Demonstrated success in working with both IT and business while integrating analytics and data science output into business processes and workflows
• Strong experience with various Data platforms like Azure Data Lake, Synapse, and Databricks
• Strong experience in working with large, heterogeneous datasets in building and optimizing data pipelines, pipeline architectures and integrated datasets using traditional data integration technologies including ETL/ELT, data replication/CDC, message-oriented data movement, API design and access
• Strong experience with popular database programming languages including SQL, PL/SQL, others for relational databases and certifications on NoSQL/Hadoop oriented databases
• Strong experience in working with DevOps capabilities like version control, automated builds, testing and release management capabilities using tools like Git, Jenkins, Puppet, Ansible.
• Basic experience working with popular data discovery, analytics and BI software tools like Tableau, Qlik, PowerBI and others for semantic-layer-based data discovery.

What we offer:

• Competitive salary and bonus
• Benefits and Pension Plan
• Product Allowances & Safe Ride Home Program
• An organization that cares about Corporate Social Responsibility
• Tuition reimbursement
• Training & Development Programs
• An opportunity to learn about the world of wine
  

#LI-Hybrid #LI-KT1

We are committed to establishing a qualified workforce that reflects the diverse population it serves and we encourage applications from all qualified individuals. We are also committed to preventing and removing barriers to employment for people with disabilities, and we invite you to inform us should you have any accessibility or accommodation needs.