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Data Engineer, Attribution Jobs

Company

Afterpay

Address , Atlanta, Ga
Employment type FULL_TIME
Salary
Expires 2023-10-03
Posted at 9 months ago
Job Description

Company Description

Since we first opened our doors in 2009, the world of commerce has evolved immensely – and so has Square. After enabling anyone to take a payment and never miss a sale, we saw sellers stymied by disparate, outmoded products and tools that wouldn’t work together. So we expanded into software and started building integrated, omnichannel solutions – to help sellers sell online, manage inventory, run a busy kitchen, book appointments, engage loyal buyers, and hire and pay staff. And across it all, we’ve embedded financial services tools at the point of sale, so merchants can access a business loan and manage their cash flow all in one place.

Today, we’re a partner to sellers of all sizes – large, enterprise-scale businesses with complex commerce operations, sellers just starting out, as well as merchants who began selling with Square and have grown larger over time. As our sellers scale, so do our solutions. We all grow together.

There is a massive opportunity in front of us. We’re building a business that is big, meaningful, and lasting. And we are helping sellers around the world do the same.

The Decision Science organization at Square helps our sellers and our business grow by empowering decision making with data. The team provides Square with a variety of critical information such as go-to-market channel attribution, investment ROI calculation, merchant value measurement, product behavior analytics, and funnel performance. We achieve this by building remarkable data infrastructure, best-in-class analytics, data science, and machine learning solutions.


We are looking for an experienced Data Engineer with a track record of delivering scalable and robust data solutions (just like you!) to join our efforts in building Square’s next generation attribution system. This system will be used by the executive leadership team to make strategic go-to-market investment decisions that will shape Square's future.


You will:

  • Monitor daily execution, diagnose and log issues, and fix business critical pipelines to ensure SLAs are met with our internal stakeholders
  • Develop and implement data quality checks to ensure data integrity
  • Perform data modeling and design of database structures for storing and processing large volumes of data with scalability and robustness
  • Work with Data Scientists and Machine Learning Engineers to identify and integrate statistical and machine learning attribution models
  • Continuously evaluate and improve the performance and scalability of the data infrastructure
  • Build and maintain data integration workflows and pipelines
  • Design and implement data pipelines to power the data driven attribution system that will fuel Square’s growth
  • Evaluate new data sources to understand the impact of integrating new data into attribution pipelines and models

Qualifications

  • Understanding of data quality management and data governance best practices
  • Familiarity with version control systems like Git and code repositories like GitHub
  • 5+ years of data engineering experience
  • Experience with SQL and other relational database management systems (RDBMS) such as Snowflake, BigQuery, Redshift
  • Strong analytical and problem-solving skills, as well as the ability to work with large and complex datasets.
  • Track record of building and maintaining large scale data pipelines
  • Knowledge of containerization technologies like Docker and container orchestration platforms like Kubernetes
  • Proficiency in programming languages such as Python, Java, or Scala
  • Familiarity with cloud computing platforms such as AWS, GCP, or Microsoft Azure, including services like S3, EC2, Dataflow, Databricks or EMR
  • Experience in designing and implementing ETL (Extract, Transform, Load) pipelines for data ingestion with ETL scheduling technologies such as Airflow and Prefect
  • Knowledge of distributed computing, big data processing, and stream processing technologies such as Hadoop, Spark, and Kafka
  • Expert level understanding of data modeling methodologies

Additional Information

Block takes a market-based approach to pay, and pay may vary depending on your location. U.S. locations are categorized into one of four zones based on a cost of labor index for that geographic area. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. These ranges may be modified in the future.

Zone A: USD $152,100 - USD $185,900
Zone B: USD $144,500 - USD $176,700
Zone C: USD $136,900 - USD $167,300
Zone D: USD $129,300 - USD $158,100

To find a location’s zone designation, please refer to this resource. If a location of interest is not listed, please speak with a recruiter for additional information.

Full-time employee benefits include the following:

  • Learning and Development resources
  • Healthcare coverage (Medical, Vision and Dental insurance)
  • Wellness programs, including access to mental health, 1:1 financial planners, and a monthly wellness allowance
  • Paid parental and caregiving leave
  • Employee Stock Purchase Program
  • Health Savings Account and Flexible Spending Account
  • Paid time off (including 12 paid holidays)
  • Paid sick leave (1 hour per 26 hours worked (max 80 hours per calendar year to the extent legally permissible) for non-exempt employees and covered by our Flexible Time Off policy for exempt employees)
  • Additional Perks such as WFH reimbursements and free access to caregiving, legal, and discounted resources
  • Retirement Plans including company match
  • Paid Life insurance, AD&D, and disability benefits

These benefits are further detailed in Block's policies. This role is also eligible to participate in Block's equity plan subject to the terms of the applicable plans and policies, and may be eligible for a sign-on bonus. Sales roles may be eligible to participate in a commission plan subject to the terms of the applicable plans and policies. Pay and benefits are subject to change at any time, consistent with the terms of any applicable compensation or benefit plans.

US and Canada EEOC Statement

We’re working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Block is a proud equal opportunity employer. We work hard to evaluate all employees and job applicants consistently, without regard to race, color, religion, gender, national origin, age, disability, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.

We believe in being fair, and are committed to an inclusive interview experience, including providing reasonable accommodations to disabled applicants throughout the recruitment process. We encourage applicants to share any needed accommodations with their recruiter, who will treat these requests as confidentially as possible. Want to learn more about what we’re doing to build a workplace that is fair and square? Check out our I+D page.

Additionally, we consider qualified applicants with criminal histories for employment on our team, and always assess candidates on an individualized basis.


Block, Inc. (NYSE: SQ) is a global technology company with a focus on financial services. Made up of Square, Cash App, Spiral, TIDAL, and TBD, we build tools to help more people access the economy. Square helps sellers run and grow their businesses with its integrated ecosystem of commerce solutions, business software, and banking services. With Cash App, anyone can easily send, spend, or invest their money in stocks or Bitcoin. Spiral (formerly Square Crypto) builds and funds free, open-source Bitcoin projects. Artists use TIDAL to help them succeed as entrepreneurs and connect more deeply with fans. TBD is building an open developer platform to make it easier to access Bitcoin and other blockchain technologies without having to go through an institution.