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ING

Data Analyst – Central Data Office (Marketing Technology)

ING is hiring a Data Analyst – Central Data Office (Marketing Technology). Level rates it ; you can apply on Level.

AI in this role

Data Analyst within ING's Central Data Office focusing on scalable marketing technology data practices and standards.

data-analysismarketing-technologydocumentationstakeholder-managementdata-governance

Data Analyst – Central Data Office (Marketing Technology)
As a Data Analyst within the Central Data Office, you contribute to building scalable data practices across ING. You support the organization-wide development and adoption of data capabilities for the Data Analyst community and work closely with Product Leads, Martech, Analytics and business stakeholders.


Your focus is on enabling consistency, collaboration and continuous improvement of data processes, tooling, documentation and knowledge sharing. You combine analytical expertise with strong collaboration skills to ensure data practices are scalable, reusable and aligned across the organization.


The team
The Central Data Office within the Martech Area enables scalable, data-driven marketing and analytics capabilities across the organization. The team ensures consistency, reusability and future-proof solutions for digital channels, while strengthening shared data practices and standards across tribes, markets and teams.


You will collaborate with data specialists, marketers, analytics colleagues, product leads and business stakeholders to strengthen ING's data capabilities and support fact-based decision-making across the organization.


Roles and responsibilities
In this role, you will contribute to the development and adoption of scalable data capabilities and ways of working across ING by:

  • Supporting the adoption of shared data standards, frameworks and best practices across tribes and teams.
  • Developing and maintaining documentation, guidelines and playbooks to ensure clarity, consistency and accessibility.
  • Contributing to the craftsmanship of the Data Analyst community by raising standards and integrating new data practices.
  • Translating data into actionable insights and presenting outcomes in a clear, understandable and business-relevant way.
  • Collaborating with data specialists, marketers, analytics colleagues, product leads and business stakeholders to improve data processes and tooling.
  • Actively strengthening ING's fact-based culture by sharing knowledge, seeking feedback and continuously improving ways of working.

Success factors
We hire smart people like you for your potential. Our biggest expectation is that you'll stay curious. Keep learning. Take on responsibility. In return, we'll back you to develop into an even more awesome version of yourself.

To be successful in this role, you bring:

  • A Master's degree in Analytics, Mathematics, Econometrics or a comparable quantitative field.
  • 4+ year's relevant experience.
  • Relevant experience in analytics, preferably within a large organization or financial services environment.
  • Proven experience with SQL.
  • Experience with SAS and/or Python is a plus.
  • Experience with visualization and dashboarding tools such as Cognos or Power BI.
  • Strong analytical skills and the ability to perform complex analyses with a practical, hands-on mindset.
  • Strong stakeholder management and communication skills.
  • A broad interest in data, from collection and analysis to experimentation and visualization.
  • The ability to translate complex data into clear and actionable business insights.
  • Comfort working in an agile environment and continuously learning new techniques.

Rewards and benefits
We want to make sure that it’s possible for you to strike the right balance between your career and your private life. Find out more about our employment conditions.


The benefits of working with us at ING include:

  • 25-28 vacation days depending on contract
  • Pension scheme
  • 13th month salary
  • 8% Holiday payment
  • Hybrid working
  • Personal growth and challenging work with endless possibilities
  • An informal working environment with innovative colleagues


About us
Curious about how ING empowers people and businesses to move forward?

Discover what we do and what we can offer you.


Questions?
Please visit our Frequently Asked Questions section to find some answers on questions you might have.


Contact the recruiter attached to the advertisement. Want to apply directly? Please upload your CV and motivation letter by clicking the ‘Apply’ button.

How we rate this

Data Analyst – Central Data Office (Marketing Technology) at ING rates 10 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Data AnalysisMarketing TechnologyDocumentationStakeholder ManagementData Governance

Questions you could be asked

  1. Tell me about a project where data analysis was part of your work. What did you do?
  2. Tell me about a project where marketing technology was part of your work. What did you do?
  3. Tell me about a project where documentation was part of your work. What did you do?
  4. Tell me about a project where stakeholder management was part of your work. What did you do?
  5. Tell me about a project where data governance was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: Data Analysis, Marketing Technology, Documentation, Stakeholder Management, and Data Governance. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.

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