Job Description

As a Data Engineer working on Measurement, you will be tasked with maintaining and developing critical data solutions used to understand conversion attribution and demystify holistic, cross-channel performance. You will be the technical owner of our multi-touch, cross-channel conversion attribution model and pipelines. In this role, you will directly contribute to Square’s growth, and closely inform investment within go-to-market channels across Sales, Marketing, SEO, etc. You will be uniquely positioned at the center of our attribution data, helping product, platform, and channel teams alike interpret performance and develop strategy. 

We want employees to be able to reside where they feel most creative and productive. You will be part of an org that works across pacific, central, and eastern time zone(s). In this role, you and your direct team will be primarily organized and operating within the pacific standard time zone. This role is open to all people who can be effective partners with this team, including sharing typical working hours

You will:

• Be the technical owner of Square’s multi touch attribution (MTA) pipelines maintaining and improving this business critical system
• Make data model and ETL code improvements to improve pipeline efficiency and data quality
• Monitor daily execution, diagnose and log issues, and fix business critical pipelines to ensure SLAs are met with our internal stakeholders
• Analyze new data sources and work with stakeholders to understand the impact of integrating new data into existing pipelines and models
• Own, coordinate, and tackle cross-functional problems across Marketing, Sales, Finance, Business Intelligence, Data Science, and more
• Develop tools, features, and reports using our data tech stack to empower self-service data access and augment intelligence

Qualifications

You have:

• At least 4 years experience building and supporting analytical data marts and warehouses built on columnar oriented RDBMS systems (e.g. Snowflake, BigQuery, Redshift, Vertica, etc.) 
• Technical accomplishments working with SQL, ETL scheduling technologies (e.g. Apache Airflow, prefect, etc) and experience working in python
• An expert knowledge of data warehouse architecture and hands on experience of data modeling design, building complex and scalable ETLs
• Experience with Linux/OSX command line, version control software (git), and general software development 
• Proven ability to lead cross-functional data engineering solutions that depend on the contributions of others in a variety of disciplines
• Strong written and verbal communication skills and ability to build strong relationships and influence across the organization