Sr. Data Engineer
Toronto, Ontario, Canada
Applications have closed
The Kraft Heinz Company
WHO WE ARE
We're one of the world's largest food and beverage companies and a trusted producer of high-quality, great-tasting, and nutritious foods, earning us a spot on 97% of American household tables. As the guardians of our beloved brands and the creators of innovative products, we're dedicated To Sustainably Grow by Delighting More Consumers Globally.
Today, The Kraft Heinz Company is building a new legacy by investing in a robust Digital infrastructure to revolutionize the food and beverage industry. We are on a journey to create a digitally-powered, agile-enterprise – all while honoring a 150-year heritage and a portfolio of 200 iconic brands. At the heart of this journey is our ambition to create an environment where powerful AI solutions augment humans and where small mission-based teams relentlessly pursue tangible solutions for our consumers, customers, and the enterprise.
That ambition requires us to create a modern cloud and data ecosystem - a one of its kind that becomes the neural network of our company. We want you to bring your tech-self to us. We use Python, R, Spark, React, Tableau, Snowflake, Azure, and others to solve our business challenges. You can look forward to high-impact, no bureaucracy, entrepreneurial work – done in small teams – and a unique opportunity to create something bold, something awesome, something inventive -- and something globally impactful.
WHAT YOU’LL DO
As a Data Engineer, you will work closely with a multidisciplinary agile team to build high quality data pipelines driving analytic solutions. These solutions will generate insights from our connected data, enabling Kraft Heinz to advance data-driven decision-making capabilities across the enterprise. You will have a deep understanding of data architecture, data engineering, data analysis, and reporting -- and a basic understanding of data science techniques and workflows, as well as the business processes supported by the data pipeline. Examples of problems you will tackle include helping R&D determine the next generation of household products, revolutionizing consumer engagement with personally relevant content, and reinventing our supply chain to eliminate food waste. Furthermore, you will:
- Design, develop, optimize, and maintain data architecture and pipelines that adhere to ELT principles and business goals
- Solve complex data problems to deliver insights that helps our business to achieve their goals
- Create data products for Business Intelligence Engineers, Business Analyst and data scientist team members to improve their productivity
- Advise, consult, mentor and coach other data and analytic professionals on data standards and practices
- Foster a culture of sharing, re-use, design for scale stability, and operational efficiency of data and analytical solutions
- Lead the evaluation, implementation and deployment of emerging tools and process for analytic data engineering in order to improve our productivity as a team
- Develop and deliver communication and education plans on analytic data engineering capabilities, standards, and processes
- Partner with machine learning engineers, business intelligence engineers and solutions architects to develop technical architectures for strategic enterprise projects and initiatives.
- Learn about machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics.
WHO YOU ARE
- Bachelor’s degree required; Computer Science, MIS, or Engineering preferred
- 5+ years of experience working in data engineering or architecture role, 7+ preferred (3 years with 5 preferred for Jr. role)
- Expertise in ELT and data analysis and experience with SQL and at least one programming language (Python/R preferred)
- Experience developing and maintaining data warehouses in big data solutions e.g. Snowflake
- Experience with developing solutions on cloud computing services and infrastructure in the data and analytics space (preferred)
- Database development experience using Hadoop, SPARK or BigQuery and experience with a variety of relational, NoSQL, and cloud database technologies
- Worked with BI tools such as Alteryx, Tableau, Power BI, Looker
- Conceptual knowledge of data and analytics, such as dimensional modeling, ELT, reporting tools, data governance, data warehousing, structured and unstructured data.
- Big Data Development experience using Hive, Impala, Spark and familiarity with Kafka (Preferred)
- Familiarity with the Linux operating system
- Exposure to machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics
- An agile learner who brings strong problem-solving skills, and enjoys working as part of a technical, cross functional team to solve complex data problems
- A hard worker and consensus gainer who brings a strong numbers sense; you are intellectually curious and willing to adjust your position based on additional information
WHY US?
We're accelerating our ambition to become a best-in-class Digital leader by making data-driven investments that drive smarter business decisions. We’re dedicated To Sustainably Grow by Delighting More Consumers Globally, and what we build today helps bring joy to customers, consumers, and communities around the world tomorrow. Here at Kraft Heinz, we're not afraid to challenge the status quo. We are bold. We embrace new ideas. We value diverse perspectives. And we dare to do better every single day. We reward courage in the face of uncertainty. And every day, we are transforming our industry. We are creating the future of food, and we invite you to join us.
Equal Opportunity Employer – minorities/females/veterans/individuals with disabilities/sexual orientation/gender identity
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile Architecture Azure Big Data BigQuery Business Intelligence Computer Science Computer Vision Data analysis Data governance Data pipelines Data Warehousing ELT Engineering Hadoop Kafka Linux Looker Machine Learning Mathematics NoSQL Pipelines Power BI Python R R&D React Snowflake Spark SQL Statistics Tableau Unstructured data
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