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Senior Data Engineer in Madrid

Affirm

Workplace
Onsite
Hours
Full-Time
Internship
No
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Job Description

Returnly is a B2B2C FinTech platform headquartered in San Francisco that focuses on turning returns into revenue for e-Commerce brands.  We work with over 700 brands ranging from SMB to Enterprise and we have offices in Chicago, San Francisco, and Madrid.

As a Senior Data Engineer, you will play a crucial role in our Analytics, Science and Engineering teams, building the data infrastructure that will allow the team to conduct, analyze, and consult on business decisions. You must be comfortable with a fast paced environment where you may need to shift responsibilities depending on business needs. We’re looking for someone who is willing to roll up their sleeves to help build the foundation so that we can continue to create state-of-the-art data products.

KEY RESPONSIBILITIES:

    • Build data pipelines that collect, connect, centralize, and curate data from various internal and external data sources
    • Manage and extend a reliable, effective, and scalable data infrastructure
    • Work closely with analysts, data scientists, and infrastructure and application engineers to understand business needs and design/implement/maintain scalable data analyses, applications and products
    • Partner with leadership and stakeholders to develop and execute various reporting packages and ad hoc requests
    • Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions

WHAT WE LOOK FOR:

    • BS or MS in Engineering, Computer Science, Math, Physics, Statistics or related quantitative field
    • Expert programming experience in two or more of the following: Java, Python, SQL, Bash, Ruby, Go
    • Expert SQL skills, ability to perform effective querying involving multiple tables and subqueries
    • Experience with Git
    • Track record of developing dashboards and visualizations that drive and optimize business outcomes
    • Nice to have: Experience and knowledge of statistical modeling techniques: GLM multiple regression, logistic regression, log-linear regression, variable selection, etc.
    • Nice to have: understanding of and experience using analytical concepts and statistical techniques: hypothesis development, designing tests/experiments, analyzing data, drawing conclusions, and developing actionable recommendations for business units
    • Nice to have: Experience creating and using machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
    • Experience building highly scalable solutions in real-time analysis for large data sets
    • Effective communicator who can work with stakeholders to define requirements
    • Strong analytical and problem-solving skills; attention to detail
    • Prior history of driving impact in a high-growth eCommerce/technology startup is a plus
    • The desire to improve broken processes and make your own job easier over time
    • Ability to think creatively and critically and thrive in a fast-paced, dynamic, and often ambiguous work environment
    • Strong interpersonal and communication skills, with the ability to communicate and influence effectively across various departments
    • Command of the English language, both written and spoken

 

About Affirm

  • E Commerce

  • San Francisco, CA, USA

  • 1,000 - 5,000

  • 2014

We’re excited to announce that Affirm is now a remote-first company! The majority of our roles can be accomplished anywhere in the U.S. and Canada (with the exception of Quebec). While most Affirmers will have the option to choose a remote-first accommodation, our offices in San Francisco, New York City, Pittsburgh, Chicago, and Salt Lake City will remain operational and accessible for anyone to use on a voluntary basis.

At Affirm, we’re using today’s technology to bring significant disruptive innovation to the financial industry. We focus on improving the lives of consumers by delivering simple, honest and transparent financial products.

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