Senior Data Engineer - WBAA Discovery Domain

• REQ-10115253
• 23/06/2026
• IT Engineering
• Amsterdam, Netherlands
• €5.485,70 - €8.828,03
• ING Bank

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This role was originally published on 28 May 2026.

Think Forward! Our goal is to help people advance in life and business. We are a well-established brand with strong financials, global reach, and omni-channel strategies. If you value innovation, agile principles balanced with compliance and quality, reliable service, and a practical work approach, this is the place for you.

What department?

WithinWholesale Banking Advanced Analytics (WBAA), theDiscoveryteam is a fast-paced group that partners with different areas of ING’s Wholesale Bank to explore, shape andvalidateAIopportunities.

Goalis to define,validateand prioritize the most impactful AI opportunities for WB, making the most efficient use of our limited resources. During the idea gathering we check on business impact, re-use,scalabilityandstrategic fit. The ideas withhighestpotential and priority will move to an AI discovery phase, where they will be evaluated for desirability, viability, and feasibility.

We help stakeholders clarify problems, assess data and technical feasibility, and create rapid prototypes thatdemonstratebusiness value. Successful initiatives are then prepared forbuildand enable ING’s Wholesale Bankingteams.

Role description

As anML/AI EngineerinWBAA Discovery, you turn ambiguous business questions intofeasibleanalytics solutions. You work end-to-end: from problem framing with stakeholders, to data exploration and feasibility assessments, to rapidproofs of conceptand prototypes, and finally to clear recommendations and handover packages for build teams.

You thrive in a start-up mindset: short feedback loops, iterative delivery, and making pragmatic trade-offs while staying aligned with banking standards (risk, privacy,securityand model governance). Success in this role depends on strongstakeholder management, clear communication, and comfort with uncertainty,ambiguity,often working with incomplete requirements and evolving priorities.

Do you recognize yourself in this profile:

• Strong Python programmingproficiency

• Demonstratedexpertisein AI integration, including working with large language models (LLMs) such as Gemini and Claude, implementing retrieval-augmented generation (RAG) patterns,designingand evaluating prompts, andutilizingvector databases.

• Ability to explore data quickly and assess feasibility(data availability/quality, constraints, and expected business impact).

• Data engineering skills: building scalable data pipelines andoptimisingdata processing (e.g.,Spark,Airflow, partitioning, incremental loads, performance tuning).

• Experience building rapid prototypes/PoCsand translating outcomes into clear recommendations and next steps.

• Experience designing and deploying cloud solutions,including CI/CD,containerisation(e.g., Docker)and infrastructure-as-code (e.g., Terraform).

• Experience with production-minded development (testing, monitoring/observability, reliability), even when starting from early-stage prototypes.

• Experience with APIs and service-based architectures (microservices, REST/gRPC, async programming).

• Strong stakeholder management: ability to align multiple parties, manage expectations, and communicate complex topics to technical and non-technical audiences.

• Comfortable withrapidly changing priorities of varying degrees of certainty; you proactively structure problems and drive decisions with limited information.

• Collaborative mindset: work effectively with data engineers, analysts, datascientistsand product owners in a fast-paced discovery setting. **Nice to have (but Not Required):**Even if youdon'tmeet every requirement, we encourage you to apply. Experience in these areas is a bonus:

• ML model training, validation, and experiment tracking experience

• GCPexpertise

• Familiarity withdiscoveryprocessor design sprints; strong s