Retail Data Modeling Analyst

ING Hubs Philippines (ING Hubs PH) is an international part of the ING organization delivering services to many Business Units across the world for both Wholesale Banking and Retail Banking activities. Working for ING Hubs PH means working with the most diverse workforce and where no challenge is the same.

At ING our purpose is to empower people to stay a step ahead in life and business. We believe that sustainable progress is driven by people with the imagination and determination to make a better future for themselves and those around them.

ING is changing what banking is. For you that means plenty of opportunities for personal growth in a continuously evolving environment. If this is the environment you thrive in then apply and join us in changing the future of banking!

Job Profile

As a Data Modeling Analyst you will help ING bank Australia on its mission to deliver high quality data across multiple business domains (incl. Retail Wholesale Risk and Finance) to leverage advanced analytics capabilities on the Neo data platform. You will be responsible for unifying the ingested data from various sources modeling business concepts and logical and physical data models to build and enhance foundational integrated and consumer aligned data products required for prioritized initiatives. Next to this collaboration with other tribes on topics related to data and data management and design thinking is a key element in the job.

As a Data Modeling Analyst you:

• You solve data challenges and perform intricate data analysis in a complex environment.

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

• You create conceptual logical and physical data models and data mappings based on requirements.
• You create functional design for data solutions. Within but not limited to Reporting and Analytics.
• 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 INGs policies and standards.

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

• A university (Bachelors/Masters) degree
• You have a 7 years of experience working in Data Warehousing / Engineering preferably in Banking industry.
• At least two years of experience designing and delivering data engineering solutions with PySpark in Azure
• End to end experience on data pipelines using on-premises or cloud-based (preferably AZURE) data platforms.
• Intermediate understanding and experience around Data Management Data Mesh / Data Products Data modeling techniques Data Architecture Data Mapping Data Profiling with Agile way of Working.
• Advanced knowledge and hands-on experience with SQL on Data Warehouse Big Data.
• Self-starter with a good ability to work in a global team across various locations.
• Knowledge on basic banking concepts is a plus particularly on Retail Banking.
• 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.

If youd like to work with:

• Data Management Experts
• Data Modelers
• Financial Experts and Stakeholders
• Actively collaborating within the Data Management space

If you want to:

• Work in Makati
• Enjoy competitive compensation and allowances.
• Be part of a diverse creative and energized team