Data Information Analyst

As a Data Modeling Analyst, you:

• You help ING prevent Money Laundering and Financial Crimes globally.
• You solve data challenges and perform intricate data analysis in a complex environment.

• You collaborate with Business Data Owners, Data Stewards, and Stakeholders to elicit, examine, understand, and refine their data requirements.

• You create data models and data mappings based on requirements.
• You create functional design for data solutions.
• You support process control standards in ING related to Metadata and Data Management.
• You work well with data engineers to ensure seamless integration work.
• You perform functional testing and validation to ensure correctness and data quality.

• You support defining requirements for Data Quality, Data Lineage and Data Governance

• You give and ask for constructive feedback.
• You ensure compliance with ING’s policies and standards.

You might be the one that we are looking for if:

• A university (Bachelor’s/Master’s) degree
• You have a minimum of 5 years of working experience in IT process and/or software/technical implementations.
• Self-starter with a good ability to work in a global team across various locations.
• Intermediate understanding and experience around Data Management, Data Warehousing, Data modeling techniques, Data Architecture, Data Mapping, Data Profiling with Agile way of Working.
• Strong knowledge and hands-on experience with SQL.
• Knowledge on basic banking concepts is a plus.
• You are a strong analytical and abstract thinker.
• You are result oriented with an ability to find ways of solving or pre-empting problems.
• You can communicate effectively across persons with different skillsets and seniority levels.
• You are passionate for learning and knows to ask the right questions in coming up with business requirements.
• You are a team player – eager to learn and can coach others.
• You are an energetic & approachable professional.
• You share and adhere to the ING values of honesty, prudence, and responsibility.