Senior Data Engineer (Google Cloud, Python, SQL, PySpark)

Financial Markets Client Control (FMCC) is part of Financial Markets (FM) within ING Wholesale Banking supporting 26 countries globally.

FMCC is responsible for ensuring effective control throughout the client lifecycle, from onboarding to exit, for Financial Markets, Group Treasury, Global Capital Markets and Bank Mendes Gans. The department operates according to Agile principles and is continuously evolving towards a DevOps way of working.

Your role

As a Senior Data Engineer, you will design, build and maintain scalable, secure and governed data solutions that support FMCC's business, regulatory and control objectives. You will translate business requirements into robust data products, pipelines, data models and reporting solutions, helping stakeholders make informed decisions based on reliable data.

You will combine hands-on engineering expertise with end-to-end ownership across the full data lifecycle, from solution design and development through deployment, monitoring and support. In addition, you will contribute to strategic data, analytics and AI initiatives while helping to establish engineering standards, improve ways of working and foster a strong engineering culture.

As a senior member of the team, you will actively share knowledge, coach colleagues and promote collaboration, transparency and continuous improvement in line with ING's principles and values.

The role reports functionally to the Data Domain Area Lead in Amsterdam and hierarchically to the FMCC Data Solutions Lead in Bratislava.

What you'll do

• Design, develop and maintain scalable data pipelines and data products across ingestion, transformation, storage and consumption layers.
• Translate business and regulatory requirements into robust technical solutions, governed data models and reporting capabilities.
• Build reliable ETL/ELT processes with appropriate controls for data quality, lineage and traceability.
• Contribute to solution design and technical standards for scalable, maintainable and compliant data solutions.
• Ensure engineering quality through automated testing, code reviews, CI/CD practices, monitoring and operational ownership.
• Manage deployments of new and enhanced data solutions across development, test and production environments.
• Assess the impact of changes and support successful implementation through close stakeholder collaboration.
• Partner with analysts, product owners, data scientists and business stakeholders to prioritize work and deliver against agreed objectives.
• Maintain accurate technical documentation, design decisions and operational procedures.
• Explore opportunities to leverage data assets for advanced analytics and AI-driven use cases.
• Coach and mentor team members while driving knowledge sharing and engineering excellence.