Job Application for Senior Data Engineer at Sytac

About Cboe Clear Europe

Cboe Clear Europe is a leading pan-European Central Counterparty (CCP), providing safe, efficient clearing and settlement services across Europe. As the most connected CCP in the region, we clear trades from 46 trading venues and support cash equities, ETFs, depositary receipts, and equity derivatives. Regulated by De Nederlandsche Bank (DNB) and the Autoriteit Financiële Markten (AFM), Cboe Clear Europe plays a critical role in maintaining the stability and integrity of European financial markets.

The Role

We are looking for a Data Engineer to strengthen our Risk Engine & Data Quality domain. In this role, you will design and build high-quality, reliable data pipelines that support core risk and clearing processes. You will work closely with risk specialists, engineers, and operations teams to ensure that the right data is available, correct, and fit for purpose—both in daily operations and during critical market events.

This role combines hands-on engineering, data quality ownership, and operational excellence in a highly regulated, mission-critical environment.

What You’ll Do

Design, build, and maintain scalable data pipelines supporting the Risk Engine and downstream consumers
Define what data is required, how it should be processed, and what the expected outputs should look like
Implement and enforce data quality checks, validation rules, and monitoring
Ensure successful rollout, adoption, and long-term maintainability of data products
Work hands-on with PySpark and Python in batch-oriented processing environments
Actively contribute to a strong incident management and operational culture
Perform root cause analysis during incidents and deployments: understanding why systems are built the way they are and how they can be improved
Apply and promote industry best practices around reliability, testing, and data engineering

Tech Stack

Languages: Python, PySpark
Data Processing: Spark (batch), SQL
Databases: PostgreSQL (and other relational databases)
Data & Analytics: Pandas
CI/CD & Tooling: Jenkins, Git
Architecture: Event-driven systems, batch processing, microservices-oriented environments
Cloud & Platform: Cloud-based infrastructure (provider-agnostic)
OS: Linux

The Ideal Candidate Has

Strong Python skills with a focus on readability, testability, and maintainability
Experience building batch data pipelines using PySpark or similar technologies
Solid understanding of advanced SQL (window functions, complex joins, performance tuning)
Strong Linux knowledge and comfort working in production environments
A pragmatic understanding of algorithms and data structures
A mindset focused on quality, reliability, and operational excellence

You’ll Really Stand Out If You Have

Experience with TDD, BDD, or other structured testing methodologies
Familiarity with PostgreSQL, Jenkins, Pandas, or Django
Experience with event-driven architectures, message queues, or event streaming
Exposure to microservices and/or REST-based services
Experience working in cloud environments
Prior experience in financial systems, risk platforms, or other regulated environments (nice-to-have)