Data Engineer

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.

Data Engineer

We are looking for a Data Engineer to join the Payment Engine Data team in Bengaluru, our newest Adyen office. The main goal of the Payment Engine Data (PED) team is to provide insightful data and solutions for processing payments using all of Adyen's payment options. These consist of various data pipelines between various systems, dashboards offering insights into payment processing, internal and external reporting, additional data products, and infrastructure.

The ideal candidate is able to understand the business context and relate it to the underlying data requirements. You should also excel at building top-notch data pipelines on our big data platform. At Adyen, your work as a Data Engineer will be vital in forming our data infrastructure and guaranteeing the seamless flow of data across various systems.

What you’ll do

• Develop High-Quality Data Pipelines : Design, develop, deploy, and operate ETL / ELT pipelines in PySpark. Your work will directly contribute to the creation of reports, tools, analytics, and datasets for both internal and external use.
• Collaborative Solution Development : Partner with various teams, engineers, and data analysts to understand data requirements and transform these insights into effective data pipelines.
• Orchestrate Data Flow : Utilise orchestration tools to manage data pipelines efficiently, experience in Airflow is a significant advantage.
• Champion Data Best Practices : Advocate for performance, testing, code quality, data validation, data governance, and discoverability. Ensure that the data provided is accurate, performant, and reliable.
• Performance Optimisation : Identify and resolve performance bottlenecks in data pipelines and systems. Optimise query performance and resource utilisation to meet SLAs and performance requirements, using technologies such as caching, indexing, partitioning, and other Spark optimizations.
• Knowledge Sharing and Training : Scale your knowledge throughout the organisation, enhancing the overall data literacy.

Who you are

Data positions at Adyen :

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