As a Data Engineer, you are a full stack data engineer that loves solving business problems with data. You work with key business and product leads, analysts and data scientists to understand the business domain and how data can empower them. You engage with fellow engineers to develop better data platforms to make the process of producing data and deriving insights easy and efficient. You are passionate about the quality of the data you produce and take pride in having your data drive our business.
What you’ll do:
- Understand the business drivers and analytical use-cases and translate these to data products.
- Explore new technologies and learn new techniques to solve business problems creatively.
- Think big and drive the strategy for better data quality within Pinterest.
- Design, implement and maintain pipelines that produce business critical data reliably and efficiently using cloud technology.
- Become the voice of business within engineering, and of engineering within business.
- Create data visualizations that allow easy consumption of the data learnings and insights.
- Collaborate with many teams from Product, Engineering and Business to produce relevant data solutions that can be used across multiple use cases.
What we’re looking for:
- 2+ years of experience with big data (Hadoop, Hive, Presto, Spark, SparkSQL), scripting language (Python) and data visualization (Tableau) technologies.
- Hands-on experience in principled data warehouse design, data visualization and data pipeline design and development.
- Great communication skills. You should be able to directly communicate with senior business leaders, embed yourself with business teams, and present solutions to business stakeholders.
- Experience in working independently and driving projects end to end.
- Strong analytical skills.
Relocation Statement:
- This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
In-Office Requirement Statement:
- We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.
- This role will need to be in the office for in-person collaboration 1-2 times per half and therefore can be situated anywhere in Ontario.
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