Data Architect
Posted on 3/27/2024
Fetch

501-1,000 employees

Consumer-engagement platform rewarding shopping loyalty via receipt
Company Overview
Fetch stands out as a leading consumer-engagement platform in America, offering a unique blend of shopping rewards and consumer insights. Its user-friendly app, which rewards customers for purchasing their favorite brands and scanning their receipts, fosters a culture of savings and loyalty. Additionally, Fetch's ability to provide brand partners with a comprehensive view of shopping habits positions it as a valuable player in the retail industry, demonstrating its competitive advantage and industry leadership.
Consumer Goods
Data & Analytics

Company Stage

Series E

Total Funding

$636.9M

Founded

2013

Headquarters

,

Growth & Insights
Headcount

6 month growth

8%

1 year growth

8%

2 year growth

29%
Locations
Madison, WI, USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Python
Airflow
Apache Flink
Data Science
Apache Spark
SQL
Apache Kafka
Java
Business Analytics
Data Analysis
CategoriesNew
Data Engineering
Data & Analytics
Requirements
  • 10+ years experience in building data pipelines and managing complex data transformations
  • Solid understanding of ETL vs ELT processes, data warehouses, and data lakes
  • Advanced analytics tools such as spark, flink, and OLAP databases
  • Knowledge about message queues and event streaming (Kafka, SNS, SQS)
  • Proficient in at least one modern programming language (Go, Python, Java, Rust) and SQL
  • Infrastructure as Code and GitOps
  • Undergraduate or graduate degree in relevant field such as computer science, Data Science, Business Analytics
Responsibilities
  • Create data pipelines that efficiently process terabytes of data daily
  • Model, transform and maintain large data sets using tools such as airflow, DBT, and spark
  • Design and implement event-driven data pipelines capable of filtering, sorting, joining, and transforming data into actionable insights with minimal latency
  • Generate innovative approaches to datasets with millions of daily active users and terabytes of data
  • Implement best practices for data governance, security, and compliance
  • Design systems and frameworks to ensure higher data quality throughout the data lifecycle
  • Provide technical leadership to the data teams and coach/mentor junior team members
  • Effectively communicate product goals, progress, issues, and risks to both technical and business stakeholders
  • Stay abreast of emerging technologies, tools, and trends in data processing and analytics