Data Analyst - Wholesale Banking Analytics @ING Hubs Romania

Discover ING Hubs Romania

ING Hubs Romania offers 130 services in software development, data management, non-financial risk & compliance, audit, and retail operations to 24 ING units worldwide, with the help of over 1700 high-performing engineers, risk, and operations professionals.

We started out in 2015 as ING’s software development hub – a distinct entity from ING Bank Romania – then steadily expanded our range to include more services and competencies.

Now we provide borderless services with bank-wide capabilities and operate from two locations: Bucharest and Cluj-Napoca.

Our tech capabilities remain the core of our business, with more than 1500 colleagues active in Data Management, Touchpoint Channels & Integration, Core Banking, and Global Products.

We enjoy a flexible way of working and a highly collaborative environment, where fair and constructive feedback is encouraged.

For us, impact isn't a perk. It's the driver of our work.

We are guided and rewarded by a shared desire to make the world a better place, one innovative solution at a time. Our colleagues make it their job to do impactful things and they love doing it in good company. Do you?

The Mission:

WBAA TS Squad empowers Wholesale Bank's Transaction Service Business Unit with data expertise and analytics solutions. Transaction Services provides the entire Payments and Cash Management infrastructure for ING's international corporate clients.

Our mission is to provide a scalable insights solution to monitor Transaction Services global business and increase profitability by enabling data-driven decisions for more than 300 internal business users.

 Our 15-people strong, cross-functional team both discovers and delivers data products that combine data visualization with advanced analytics elements.

As a Senior Data Analyst, you excel at delivering high-quality data analysis while guiding and mentoring Junior and Medior analysts. You are skilled at identifying, analyzing, and interpreting patterns in complex data sets. You explore and evaluate data sources across various systems, ensuring the availability of key data for analysis.

Collaborating closely with Data Engineers and Data Scientists, you contribute to building robust analytics products. Your insights support critical business decision-making, and you effectively communicate findings to stakeholders using both analytical and business language.

Your day-to-day:

Data analysis:

• Use SQL, Python to analyze data, generate reports, and create statistics that support business decisions.

• Identify trends and patterns in data to provide actionable insights.

• Develop and maintain dashboards using visualization tools like PowerBI to present data clearly to stakeholders.

• Explore and investigate the data sources and their availability in different data consumption systems.

Business Analysis:

• Collaborate with stakeholders to understand their requirements and limitations.

• Translate these requirements into data-driven solutions that align with broader business goals.

• Ensure that solutions are scalable and adaptable to changing needs.

Adaptability and Flexibility

• Stay up-to-date with emerging technologies and industry trends.

• Be ready to learn and adapt to new tools, methodologies, and challenges in a dynamic environment.

What you’ll bring to the team:

• Experience: 3-5 years of experience in data analytics, data visualization or/and statistics

• Tech stack/ knowledge:

  • Mandatory:

    • SQL

    • Python (especially Pyspark)

    • Sound experience in data analytics/visualization tools such as PowerBI/Tableau/Cognos/Superset

    • Data reporting & statistics

  • Nice to have:

    • Experiences in working with Data Pipeline

    • Experience in Data Analytics in the financial services industry

    • Understanding in Machine Learning/AI

• Excellent communication skills, both verbally and in writing, to be able to align with various stakeholders.

• Ability to interpret and analyze data excellently, using standard techniques and tools.

• Up to date with the latest industry standards and trends in Data Analysis.

• Ability to work with large amounts of data: facts, figures, and number crunching.

• Ability to apply high level analytical, statistical, and quantitative problem-solving skills to make actionable recommendations based on outcomes.

• Ability to understand a predictive modeling used in Machine Learning/AI projects.

• Language: English (advanced).

• Education: Master’s degree in Mathematics, Economics, Computer Science, Information Management, Engineering, Statistics.