Technical Business Analyst

Discover ING Hubs Romania

ING Hubs Romania offers 130 services in software development, data management, non-financial risk andamp; compliance, audit, and retail operations to 24 ING units worldwide, with the help of over 2000 high-performing engineers, risk and operations professionals.

We started out in 2015 as ING's software development hub, 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 1800 colleagues active in Data Management, Touchpoint Channels andamp; 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

In your role you will support the organization in achieving a well governed data lake that ensures data availability, common understanding of business terms, impeccable data quality, traceable and controlled data in line with regulations. In other words, an ambitious implementation based on leading technology.

Your day to day

Even if you'll start your day from the comfort of your home or drink your morning coffee in our office's garden, your day will be quite similar when comes to tasks. Here are your daily responsibilities:

Closely collaborate with stakeholders to:

• Together with relevant stakeholders from business areas (like Financial Insights, Direct Products, Service and Operations, KYC), you contribute to understanding and clarifying the requirements
• Draw up conceptual and logical data models (different types) - you are a sparring partner for engineers for the translation of these models to the physical model
• Create detailed specifications that DevOps engineers will use to source and structure data into the Data Lake
• Create testing scenarios and actively participate in functional testing
• Safeguarding the consistency and quality of data: create requirements on data quality, data lineage, data privacy, data security, and other relevant aspects of data by recording the data definitions in the data dictionary and maintaining them as part of metadata management
• Align with the architects on the data lake design and ensure the implementation of the new solution is done according to the data lake target architecture
• Continuously take initiative to improve the way of working and the collaboration within your team and stakeholders. Actively participating in gathering the requirements for automation of our software processes

What you'll bring to the team

• 3-5 years (minimum) of experience on a similar role
• Hands-on experience working with SQL and databases and/or data warehouses is expected
• Take it on and make it happen attitude, drive to help others succeed and a knack for always being a step ahead
• Strong conceptual and analytical skills, detail-oriented
• Excellent communication skills, both verbally and in writing, to be able to align with various stakeholders on different levels
• Experience in requirements gathering and writing technical and functional specifications
• Experience with Agile methodologies
• Foreign languages: English (advanced)
• Education: nice to have Bachelor's Degree (or higher) in an IT related field
• Experience with banking industry or financial institutions is a plus
• Knowledge of and experience within the Credit Risk and Credit Risk modelling areas in the financial industry is nice to have
• Knowledge of and experience in data management, data modelling (dimensional) and data warehouse technology is a plus
• Finance, Credit Risk, Regulatory processes and Operational Risk know-how is a plus
• Hands-on experience with data quality, data lineage, data security, data privacy, data lifecycle management, data issue remediation and other data-governance practices is a plus

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