Who we are looking for?

Data Affinity: Understanding and interested in complex data and data structures.Clear Communicator: You are a communicator and like to liaise with data teams, reporting teams, UAT team and IT teams.Supporter: Act as the link between stakeholders providing data requirements and developers needing technical specifications.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.

What you need to bring:

Knowledge and interested in ETL and Data processes.Minimum 2 years of experience working in business analysis, data analytics, or data science in the banking sector (preferably ALM side).Hands-on experience working with SQL is a must-have.Familiarity with data management concepts such as data quality, data lineage, and data reconciliation.Some intuition of data requirements for ALM software, Risk, or Financial reporting.Experience in requirement gathering for data feeds.Familiarity with data models and structures.

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 maintain 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.

Understand complex data and ETL processes on the in-house data platform.Support the transformation and loading of finance data flows into QRM.Monitor and maintain the correctness of data flows.Translate (internal) Risk/Finance data requests into understandable and actionable items and designs with the team.Assist in the development of Data Quality controls and new data solutions to end-users.Support reporting teams in the development of data marts and reporting solutions 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.