Position Snapshot

Business areas: Nestlé Canada

Job title: Specialist Product Ownership-Data Engineer (1-year contract)

**Location:**North York, ON located at 25 Sheppard Ave W, North York, ON M2N 6S8;

Hybrid

A little bit about us

While Nestlé is known for KitKat, Gerber, Nescafe, and Häagen-Dazs, our recipe for success comes down to one thing: our people.

We strive to lead a people-focused culture that empowers employees to bring their authentic selves to work each day. There are 3,000+ members of Nestlé Canada celebrated for taking action using agility, courage, and trust to find solutions that benefit the business or greater good. We’re a team of changemakers, who are curious and challenge the status quo, that take risks that will help drive us forward.

Our focus is not only on nourishing our customers, but also about enriching you. We know that empowerment leads to strong employee engagement, a great work culture, and motivated employees.

Position Summary

The Data Engineeris responsible for supporting the development and optimization of data products by leveraging information modelling and programming skills. This role involves cleaning, preparing, and optimizing data for use by data scientists and UX/Visual experts, integrating cognitive computing and advanced analytics with traditional data engineering techniques. The Data Engineer designs and builds data systems from various sources, manages complex queries, and ensures the accessibility and functionality of the data ecosystem.

A day in the life of a Specialist Product Ownership-Data Engineer:

Key responsibilities include collaborating with IT Solution Architects and Data Product Owners to embed models into operations, performing product ownership activities such as stakeholder management and product lifecycle management, and continuously improving data products. The ideal candidate will have a strong background in data management, experience with structured and unstructured data, and proficiency in programming languages like Python, R, or SQL. Familiarity with data visualization tools, big data technologies, and machine learning algorithms is also essential. The role requires excellent problem-solving and communication skills in a fast-paced environment, contributing significantly to driving insights and value for the organization.

Data Engineering - Data Products

• • Cleaned and prepared data for analysis and consumption
  • Optimized the performance of the data ecosystem
  • Integrated data from various sources
  • Managed complex queries for data extraction and manipulation
  • Derived insights and performed analysis on structured and unstructured data
  • Collaborated with IT Solution Architects and Data Product Owners for embedding successful models into operations
  • Continuously improved data products based on user feedback and evolving business needs
  • Clear and concise technical documentation and architecture design.

Operational Effectiveness & Efficiency

• • Streamlined data processes: Implementing efficient and standardized data processing workflows to improve operational effectiveness.
  • Automated data pipelines: Developing automated data integration and transformation pipelines to enhance efficiency and reduce manual effort.
  • Scalable data infrastructure: Designing and implementing a scalable data infrastructure that can handle increasing data volumes and user demands.
  • Monitoring and optimization: Establishing monitoring systems to track data performance and identifying areas for optimization to improve operational efficiency.
  • Agile project delivery: Applying agile methodologies to ensure timely and efficient delivery of data products and solutions.
  • Continuous improvement: Encouraging a culture of continuous improvement to identify and implement enhancements in operational processes and workflows.
  • Collaboration and communication: Facilitating effective collaboration and communication between cross-functional teams to ensure smooth and efficient data operations.
  • Documentation and knowledge sharing: Creating comprehensive documentation and promoting knowledge sharing to enhance operational effectiveness and efficiency.
  • Performance metrics and reporting: Establishing performance metrics and reporting mechanisms to measure and communicate operational effectiveness and efficiency to stakeholders.

Stakeholder engagement

• • Develops partnerships with business stakeholders to keep them apprised about their data solution needs.
  • Works with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions and provide data sourcing advisory

Role Requirements

• Bachelor’s or master’s degree in computer science, Information Systems, Data Analytics, or a related field from a recognized institution.
• Minimum 3 years working with BIG or complex data sets in a data engineering role.
• Strong understanding of data engineering concepts, including idempotency, data modelling, ETL process and data integration.
• Demonstrated ability to articulate ideas, and effectively convey complex technical concepts to both technical and non-technical audiences.
• Knowledge of designing a transactional schema, star schema and/or snowflake schema.
• Experience with cloud-based platforms- Microsoft Azure, Azure Databricks and Snowflake.
• Expertise in working with structured and semi-structured data; apply methods, technologies and techniques that address data architecture, integration, and governance of data.
• Experience with Azure Cloud services – Azure Synapse Analytics, Data Factory, Logic Apps, Azure Data Lake Storage Gen2.
• Experience with Snowflake architecture and data ingress/egress methodologies.
• Well-versed with Delta Lake concept and medallion architecture in Databricks.
• Possess solid skills in understanding data structures in Python or Scala, SQL concepts including but not limited to ACID compliance, slowly changing dimensions and knowledge of spark including but not limited to its use case, memory management, parallelization etc.
• Experience working in Azure DevOps to adopt continuous integration and continuous delivery method.
• Knowledge of Azure Compute services, uses, and methodologies.
• Demonstrable experience with Agile projects and knowledge of Scrum techniques and artifacts (such as definition of sprint planning, planning poker, feature creation, user stories and backlog refinement)

Benefits

• Flexible and hybrid work arrangements
• Excellent training and development programs as well as opportunities to grow within the company
• Access to the Discount Company store with Nestlé, Nespresso, and Purina products (Located across various Nestle offices/sites)
• Additional discounts on a variety of products and services offered by our preferred vendors and partnerships

What you need to know

We will be considering applicants as they apply, so please don’t delay in submitting your application.

Nestlé Canada is an equal-opportunity employer committed to diversity, equity, inclusion, and accessibility. We welcome qualified applicants to bring their diverse and unique experiences as a result of their education, perspectives, culture, ethnicity, race, sex, gender identity and expression, nation of origin, age, languages spoken, veteran’s status, colour, religion, disability, sexual orientation and beliefs.

If you are selected to participate in the recruitment process, please inform Human Resources of any accommodations you may require. Nestlé will work with you in an effort to ensure that you are able to fully participate in the process.