Data Engineer in Fintech

At Fintech, we create payment products, services, and tools for personal finance management. Fintech has already evolved from a startup into a full-fledged and critically important product.

Currently, we are building a new analytical data warehouse and forming a team for it. The warehouse has no legacy, so you will have the opportunity to be at the inception of a new project. We have big plans — come help us implement them!

What tasks await you

Building ETL processes You will need to extract valuable information from sources, process it, and present it in a format convenient for analysts. The complexity of pipelines can range from simple data ingestion from external environments and landing the result in the warehouse to intricate graphs with multiple inputs and outputs.

Optimizing logic As you know, we have no legacy of our own, but we often work with prototypes implemented by analysts, whose idea of excellence may differ from ours. Therefore, we unravel non-trivial logic and propose more rigorous, consistent, and optimal solutions, focusing on large volumes of data.

Ensuring service availability The olympiad approach implies a one-time result. We pursue entirely different goals, so the maxim 'it worked once — and that's fine' is not about us. The ideal is this: the warehouse ensures regular delivery with the minimum possible number of failures, and the data is correct, complete, consistent, and meets the strictest quality standards.

Designing the warehouse structure The best analytical DWH is still just on the drawing board. We want to lay the foundations that will allow it to evolve quickly, acquiring not 'crutches' and 'reinvented wheels', but modern engineering practices and approaches.

Collaborating with analysts They are our main and beloved customers. Together with them, you will contemplate business tasks, sometimes you will argue, but in the end — find optimal solutions. An integral part of this process is accumulating personal experience in the Fintech business domain. Add to that the growth of engineering experience — and you get double the benefit. Almost like with Yandex Pay.

We expect that you

• Confidently program in Python
• Have a good knowledge of SQL and understand the architecture of modern DBMS
• Understand and can explain the necessity of continuous integration and delivery (CI/CD), the advantages of using version control systems, code review, testing, and monitoring
• Work in the command line of Unix-like systems (Linux, macOS)

It will be a plus if you

• Have created complex, high-load ETL and ELT processes (Hadoop, Hive, Spark)
• Have developed near real-time event processing processes (Kafka, Spark Streaming, Flink)
• Participated in data warehouse design
• Have worked using Agile methodology
• Have mentored interns or junior specialists
• Are familiar with specialized analytical databases (Greenplum, Vertica, ClickHouse, Teradata) and analytical tools based on Python (Jupyter, pandas, SciPy, Matplotlib)
• Publish your code in an accessible repository, write articles, speak at conferences