Staff Software Engineer, Data

Posted 12 Days Ago
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Chicago, IL
7+ Years Experience
Fintech • Payments • Financial Services
Adyen is the financial technology platform of choice for leading companies across the globe.
The Role
Staff Software Engineer role at Adyen's Data Connect team in Chicago, focusing on building innovative data products for enhancing customer understanding. Responsibilities include setting architecture direction, designing data pipelines, collaborating with cross-functional teams, and leveraging machine learning algorithms.
Summary Generated by Built In

This is Adyen

Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H&M, and Microsoft - making us the financial technology platform of choice. At Adyen, everything we do is engineered for ambition. 

For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster.


This is Data Connect

We are hiring a Staff Software Engineer for the Data Connect team in Chicago. This team is part of Adyen's Data Solution strategy of developing data products to enhance our customer’s understanding of their shoppers. We're looking for trailblazers with an entrepreneurial mindset to innovate, tinker, and craft something entirely new from the ground up.

We believe in the transformative power of data. Data is not just a byproduct; it's our driving force, shaping the way we understand our business and deliver innovative solutions to our customers. Within our team, you'll tackle high-impact projects that all revolve around understanding our client's customers. These include developing shopper recognition, attribution, and profiling products. You'll work closely with engineering and product teammates to quickly iterate across every phase of the product life cycle, from evaluating product-market fit to release.

The Data Connect team is building a shopper recognition product for the biggest brands in the world. You will work on a low-latency, highly available service and run fancy graph algorithms in parallel over tens of billions of data points in Spark. Help us push the boundaries and find the optimal trade-offs between latency, recency, quality, and reliability.


Staff Software Engineer, Data

We are building products that have never been made before. As a critical member of the team, you will also help build the Data Connect team from scratch by partnering with Engineering and Product leaders to hire Data Scientists, Data Engineers, and Software Engineers. As a Staff Engineer focusing on data, you will play an instrumental role in the Data Connect team. This role is pivotal in advancing our data-driven initiatives and contributing to the creation and enhancement of our global data product suite. 

We seek a passionate and experienced Staff Engineer who is uniquely energized by data as a product. We envision someone who can go beyond traditional data handling, exploring innovative ways to transform our data into impactful products that offer our customers unprecedented insights from their first-party data.


What you'll do

  • You will be a key voice in setting the direction of the architecture and the solution of our Data Connect product.
  • You will be at the forefront of translating business needs into robust data pipelines, designing and implementing data products, and ensuring the overall quality and performance of our data solutions.
  • You will collaborate closely with Data Scientists, Data Engineers, Backend and Frontend Engineers to design and build high-quality data products and tooling.
  • You will obtain insights by leveraging machine learning algorithms, including clustering algorithms to group customers/shoppers, supervised and semi-supervised learning methods for inference on shopper behavior and graph analysis, and representation learning for behavior prediction and monitoring.
  • You will accelerate decision-making and act as a multiplier and enabler for technical matters across the global organization.
  • You will think long-term and lean on experience to aid teams that are blueprinting, defining, or redefining architectures and data models.
  • You will mentor and guide engineers to improve their technical skills and make informed decisions.


Who you are

  • You are a technical leader with 10+ years of professional experience, including 2-3 years in a technical leadership role like Staff Engineer, Principal Engineer, or Architect.
  • You have 8+ years of experience in the implementation of data projects like data warehouses, data lakes, operational data stores, data modeling, data architecture, as well as data integration methodologies and patterns.
  • You have extensive experience with big data frameworks, statistical testing, and machine learning algorithms.
  • You have solid engineering principles of performance, code quality, data validation, governance, and discoverability.
  • You have excellent communication skills and are able to convey complex outcomes to a wide range of audiences.
  • You are skilled at collaborating with a variety of people, including cross-functional teams, non-technical stakeholders, and senior leaders. You excel at bringing people together to align on solutions, and care about finding the best idea, no matter whose idea it is.
  • You are familiar with technologies such as Java, Spark, Scikit-Learn, TensorFlow, PyTorch, XGBoost, Pandas, and Airflow.


Our Diversity, Equity and Inclusion commitments 

Our unique approach is a product of our diverse perspectives. This diversity of backgrounds and cultures is essential in helping us maintain our momentum. Our business and technical challenges are unique, and we need as many different voices as possible to join us in solving them - voices like yours. No matter who you are or where you're from, we welcome you to be your true self at Adyen. 

Studies show that women and members of underrepresented communities apply for jobs only if they meet 100% of the qualifications. Does this sound like you? If so, Adyen encourages you to reconsider and apply. We look forward to your application!


What's next?

Ensuring a smooth and enjoyable candidate experience is critical for us. We aim to get back to you regarding your application within 5 business days. Our interview process tends to take about 4 weeks to complete, but may fluctuate depending on the role. Learn more about our hiring process here. Don't be afraid to let us know if you need more flexibility.

Adyen is an equal opportunity employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status or any legally protected status.

All your information will be kept confidential according to EEO guidelines.

This role is based out of our Chicago office. We are an office-first company and value in-person collaboration; we do not offer remote-only roles.

Top Skills

Java
Spark

What the Team is Saying

Isabelle
Sebastian
Angel
Mika
The Company
HQ: Amsterdam
4,196 Employees
Hybrid Workplace
Year Founded: 2006

What We Do

By providing end-to-end payments capabilities, data-driven insights, and financial products in a single solution, Adyen helps businesses achieve their ambitions faster.

Our team members are motivated individuals from different cultures that help each other do remarkable things every day and across time zones. We face unique technical challenges at scale and we solve those as a team. And together, we deliver innovative and ethical solutions for businesses all across the world.

With 27 offices across the globe, Adyen serves customers including Meta, Uber, Spotify, Casper, Bonobos and L'Oreal.

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Adyen Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

Typical time on-site: Flexible
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