Sr Data Engineer
BR São Paulo, São Paulo, Brazil
Farfetch
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ROLE & IMPACTWorking on Data Engineering your role will be focused on creating access to critical data for a variety of teams, spread across the business and engineering groups. Stadium Goods is an international organization with diverse data from across multiple platforms (including stores) and your work will directly help the organization create value from that data. You will use a variety of techniques, ranging from structuring data for Tableau and creating the perfect report for broad consumption or writing APIs for the engineering team to consume data in a structured way.
You will join other data engineers who are building out the practice and you’ll have the freedom to explore new ways of thinking about these challenges and have the potential to make a significant impact on the way the business operates using data.
WHO YOU AREYou understand the importance of process and structure but also know how to get things done in a scrappy way.You’ve worked with a variety of types of data and know how to make things come together to form a cohesive dataset.You are ready to answer the big questions about what’s working and what’s not, but also have the patience and focus to dig in on why a certain piece of data may or may not be correct due to technical issues.You are ready to work closely with a variety of stakeholders to get things done and can explain problems from outside people’s experience in a way that helps them understand and feel engaged.
RESPONSIBILITIESCreate and maintain optimal data pipeline architecture;Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.Build systems that allow for validation of our data product, ensuring accuracy of these data sets.Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.Build analytics tools that utilize the data pipeline to provide actionable insights
Requirements2-5 years’ experience working in Data Engineering.A foundation in Computer Science, Engineering, Stats, or Math, through education and/or work.Advanced SQL skills.Strong Python or R, and Tableau skills.Experience with AWS or Azure cloudsLinux/Unix experience preferred.Prefer experience working in ecommerce (bonus points if you’ve worked with eBay, Amazon, or Tmall)Experience with Airflow, DBT, or similar tools for managing ETL pipelines.Bonus for working on international commerce.Ability to make thoughtful trade-offs among a diverse set of teams and priorities, filling the gap between business requirements and engineering, and suggesting reasonable workarounds when necessary.Bonus points if you have a passion for the sneaker and streetwear industry
You will join other data engineers who are building out the practice and you’ll have the freedom to explore new ways of thinking about these challenges and have the potential to make a significant impact on the way the business operates using data.
WHO YOU AREYou understand the importance of process and structure but also know how to get things done in a scrappy way.You’ve worked with a variety of types of data and know how to make things come together to form a cohesive dataset.You are ready to answer the big questions about what’s working and what’s not, but also have the patience and focus to dig in on why a certain piece of data may or may not be correct due to technical issues.You are ready to work closely with a variety of stakeholders to get things done and can explain problems from outside people’s experience in a way that helps them understand and feel engaged.
RESPONSIBILITIESCreate and maintain optimal data pipeline architecture;Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.Build systems that allow for validation of our data product, ensuring accuracy of these data sets.Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.Build analytics tools that utilize the data pipeline to provide actionable insights
Requirements2-5 years’ experience working in Data Engineering.A foundation in Computer Science, Engineering, Stats, or Math, through education and/or work.Advanced SQL skills.Strong Python or R, and Tableau skills.Experience with AWS or Azure cloudsLinux/Unix experience preferred.Prefer experience working in ecommerce (bonus points if you’ve worked with eBay, Amazon, or Tmall)Experience with Airflow, DBT, or similar tools for managing ETL pipelines.Bonus for working on international commerce.Ability to make thoughtful trade-offs among a diverse set of teams and priorities, filling the gap between business requirements and engineering, and suggesting reasonable workarounds when necessary.Bonus points if you have a passion for the sneaker and streetwear industry
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Airflow APIs Architecture AWS Azure Big Data Computer Science E-commerce Engineering ETL Mathematics Pipelines Python R SQL Tableau
Region:
South America
Country:
Brazil
Job stats:
3
1
0
Category:
Engineering Jobs
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