Data Engineer - Analytics @ ING Bank

About the role

You'll join the Analytics Centre of Expertise within the Customer Interactions Tribe , a collaborative, multidisciplinary environment bringing together Data Engineers, Data Analysts, Data Scientists and IT partners. The team combines technical expertise with analytical thinking and a strong business understanding. We work in an open, Agile setup where curiosity, ownership and continuous learning drive our day‑to‑day work. Your day to day Your responsibilities include: Evaluating data sources, flows and tools to identify gaps and recommend optimal solutions for analytics and data science needs Analyzing and optimizing databases and data processes, including scripting for maintenance, monitoring and performance tuning Applying your expertise in database design, administration and optimisation to ensure accuracy, performance and resilience Using your knowledge of operating systems (Windows and/or Linux) to automate, maintain and troubleshoot data workflows Leveraging networking concepts to enable secure and efficient data transfers across systems Working with complex data elements and dependencies to support the development of scalable data models Creating reusable scripts, data flows and methodologies to improve analytics speed and reliability Documenting all data pipelines, processes and technical decisions to ensure consistency and quality Managing recurring data processing flows and ensuring they meet established SLAs and quality standards Recommending improvements for application software and infrastructure to enhance performance and reliability Acting as a main technical contact for IT partners, ensuring system resilience, security and compliance Developing and maintaining data privacy and security procedures, always adhering to ING's ethical standards What you bring to the team 1-3 years of experience as a Data Engineer , ideally in analytics‑driven or data‑intensive environments Hands‑on experience with Python for data processing, automation and scripting; exposure to Spark / PySpark is a strong plus Solid experience working with SQL for data extraction, transformation and analysis; exposure to SAS is a plus Experience delivering data pipelines and ML‑enabled use cases , using technologies such as Spark, Pandas and NoSQL / big data platforms Bachelor's degree in IT, Computer Science, Cybernetics, Automation or a related technical field Basic understanding of data modeling, database design, administration and performance optimization Practical experience with Windows and/or Linux environments , including automation, monitoring and troubleshooting Basic understanding of networking and security concepts , to support secure and reliable data flows A data‑driven mindset and strong digital fluency, with attention to data quality, reliability and governance Clear communication skills , able to collaborate effectively with Data Analysts, Data Scientists and IT partners Ability to build structured, reusable processes and work in a disciplined, production‑oriented way Team‑oriented attitude , curiosity to learn new technologies and the confidence to make decisions Ability to manage complexity and synthesize large datasets into usable data products Strong delivery mindset , with ownership from development to production and a customer‑centric approach English proficiency - above medium level , for technical documentation and cross‑team collaboration