Specialist Product Ownership, Data Engineer (12-months contract)

Specialist Product Ownership-Data Engineer (1-year contract)

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

Compensation Range: $85000 - $95000

At Nestle Canada we are committed to transparency and fairness in our compensation and job posting practices. This position offers a competitive salary within the range specified above in compliance with Ontarios pay transparency regulations.

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 3000 members of Nestlé Canada celebrated for taking action using agility courage and trust to find solutions that benefit the business or greater good. Were 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 Engineers 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
Bachelors or masters degree in computer science Information Systems Data Analytics or a related field from a recognized institution.
Minimum 2 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 dont 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 veterans 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.

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