Who we are looking for?

Data Practitioner: Experienced in managing and understanding complex data and data structures, and how they contribute within ALM risk and Balance Sheet Management.Clear Communicator: You are a communicator and like to liaise with stakeholders such as IT teams, Finance reporting teams, UAT team and other ING HUBS.Connector: Act as the link between stakeholders providing functional data requirements and translate this with the developers to technical specifications.Project Manager: You possess project management skills.Team Player: Someone with a “can-do” mentality who excels in a collaborative environment. You are a problem solver.International Team Player: You enjoy working in an international team and environment.Proactive Learner: You are proactive and eager to learn.Strong Analyst: You have strong analytical skills.Analytical Innovator: A strong analytical thinker who can create, challenge and enhance data processing techniques.

What you need to bring:

Familiarity with IRRBB / Liquidity regulatory environment.Experience working in Market Risk or Trading Risk within the banking sector.Minimum 5 years of experience working in business analysis, data analytics, or data science in the banking sector (preferably ALM side).Knowledge in Data and ETL processes and concepts with SQL.Knowledge of data requirements for ALM software, Risk, or Financial reporting.Experience in development/requirement gathering for data feeds.

You’ll get extra points for:

Experience in Asset and Liability Management or any Risk control/modeling function.ALM Risk knowledge, understanding a bank balance sheet, and being able to connect the dots between the data and the ALM reporting outcome.Familiarity with any ALM software (i.e., QRM, Fusion Risk, OneSumX, Moody’s Analytics).Reporting skills, preferably in PowerBI.Master’s degree in econometrics, mathematics, economics, IT, or a similar quantitative study.Experience in Agile (Scrum) methodologies.

Your responsibilities:

In the role of ALM Data analyst you will be required to quickly understand complex data and ETL processes. You will build new functionality to process and handle big data streams. The ALM data is mainly used for Net Interest Income (NII) forecasting, valuation and replication (i.e. hedging). You will be working on both the business and IT side of the ALM processes and must be able to translate functional requirements from business analyst into technical solutions.

Quickly understand complex data and ETL processes on inhouse data platform,Translate Risk/Finance data requests into actionable items and designs with the team,Implementation new solutions to end-users and locations.Lead a project to improve data technics and Data Quality ControlsSupport reporting teams in development of data marts and reporting solution in PowerBI.

Information about the squad:

Dynamic International Team: Comprising around 90 ALM specialists based in Amsterdam (NL), Warsaw (PL), and Manila (PH). This position is specifically located in Warsaw.Growing Warsaw Office: The expanding role of our Warsaw office is driving the demand for fresh talent.Agile ALM Project Teams: We operate in Agile teams that include Market Risk Management, TECH Developers, ALM Data Experts, ALM Business Analysts, and QRM Experts.Unified Implementation: ING Bank is standardizing the implementation for Interest Rate Risk, Liquidity Risk and Forecasting across its banking books, driven by regulatory requirements and internal risk management insights.Collaborative Culture: We prioritize mutual support, knowledge sharing, teamwork, and continuous improvement, both professionally and personally.Young and International: Our team is youthful and globally oriented, focusing on developing new functionalities and methodologies for our ALM platform.Stakeholder Relations: The role involves supporting ING’s headquarters, with success hinging on maintaining strong relationships with end-users and stakeholders, including Financial Risk teams, local Risk Managers, and Finance teams.Data-Driven Solutions: We handle Finance and ALM Risk data, collaborating with internal and external stakeholders to find optimal structural solutions for ING globally. Experience with Finance systems, particularly in ALM or Treasury-related data, is highly valued.