Data Engineer II

Department: Product Analytics & Data Science Job

Category: Engineering / Infrastructure 



Duties: The Business Intelligence (BI) team is looking to hire a Data Engineer to build robust, extensible, and scalable data and BI solutions for Pinterest's product org. These solutions could be a combination of one or more of the following: source-of-truth datasets, daily/hourly pipelines, dashboards, visualization tools, and alerting.



This role will entail the following responsibilities:

Understand the data landscape of Pinterest products Design, architect, and implement new source of truth datasets, in partnership with analytics and business teams

Build the required data and reporting pipelines using Pinterest's internal ETL tools Develop dashboards, web-based visualizations (using Tableau, D3, or Plotly), and web-based tools (node.js or flask apps)

Collaborate with other engineering teams to develop and integrate BI solutions

 

Skills:

Experience designing, architecting, and maintaining data warehouses that seamlessly stitches together data from production databases and clickstream event data

Hands-on experience with Hive query development and optimization, and, building workflows (preferably using Airflow)

Hands-on experience with building data pipelines in a programming language like Python

Hands-on experience with building and maintaining Tableau dashboards and/or Jupyter reports

Working understanding of Hadoop and Big data analytics Ability to understand the needs of and collaborate with stakeholders from analytics and business teams



Education:

Bachelors or Masters degree in Computer Science, Engineering, Management Information Systems, or a related quantitative/analytics discipline and at least three (3) years of experience in the field of data engineering or business intelligence/analytics



Required Skills:

PYTHON

HIVE

ETL

BIG DATA ANALYTICS

DATA WAREHOUSE DESIGN/ARCHITECTURE

Tableau dashboards and/or Jupyter reports 

ENGINEER

DATA VISUALIZATION

AWS

Tableau, D3, or Plotly

node.js or flask apps



Preferred:

Airflow