How do you make our customers happy?
All our colleagues want to use data to improve the quality of their decisions to positively impact our customers’ lives and partners’ businesses. We are building a self-service data architecture that empowers teams to satisfy their data needs autonomously — and now we are taking the next step: making our Data Platform intelligently proactive, delivering personalized insights to the people who need them, when they need them.
In this context, the Data, Analytics & AI department is evolving bol’s Data Platform from infrastructure into an intelligent analytics layer. We serve the entire bol organization, where every department or domain has its own challenge. How do you move beyond dashboards toward agentic analytics, systems that surface relevant insights, answer questions conversationally, and act on behalf of users? How do you do that in a decentralized setup, with enthusiastic data engineers and analysts who want state-of-the-art tools but also have to comply with rules & regulations? How do we get qualitative insights on the effectiveness of our product teams to decision makers, without them having to go looking?
Can you help us achieve this goal?
The biggest challenge
Our Data department is taking the Data Platform to the next level. A huge challenge because we serve the entire organization, and every department presents unique data challenges.
How can we build an analytics experience that feels personal — where insights find the user, not the other way around?
How can we empower enthusiastic analysts who want to push agentic and conversational tools to their full potential while still complying with all applicable rules and regulations?
How can we inspire engineers to make data easily accessible, semantically rich, and ready for intelligent consumption?
And what options should we explore to monetize our data and intelligence capabilities internally and externally?
Where do you land?
The Data Engineering Platform builds our internal data platform foundation and enables it to scale. As a platform team it builds components to enable engineers work with data efficiently in a standardized way. The Data, Analytics & AI department foresees opportunities to establish a platform where data can be easily found, is reliable and compliant and of high quality, while ensuring data availability.
This team is part of Data Analytics & AI department, together with other IT teams, in a highly multicultural environment, with engineers from all over the world. All teams work closely with product managers, lead engineers and tech architects.
Team’s vision
Team’s vision is to enable data and AI use cases for users to independently build and operate data products by providing standardized, opinionated tooling, clear abstractions, and guardrails for security, compliance, and cost. Some parts are already in place and it is expected from the new team member to help us figure out which components need to be added to build a reliable set of tools to serve data. This role is made for a highly driven Engineer with strong Kotlin and Java skills and thrives in the face of change and uncertainty.
The role
The Software Engineer will play a critical role in designing, developing, and maintaining robust data infrastructure to support a scalable and efficient internal data platform. You will design and deliver core data platform capabilities such as standardized ingestion frameworks, data quality and observability tooling, metadata and governance services, and enable data to be consumed by both analytical workloads and AI-driven applications.
The software engineer that the team needs is a software engineer who is eager to understand the complexity of creating tools used by hundreds of teams.
You combine your deep technical expertise with the ability to make complex concepts accessible to a diverse audience.
Key responsibilities
Platform Development and Maintenance
- Define, build and maintain the internal data platform to support data ingestion and data quality.
- Enable self-serve capabilities of the data platform
- Ensure the platform’s cost efficiency, performance, and security.
Collaboration and Integration
- Work in close cooperation with cross-functional teams, like Platform Teams, Security Department, Analytics Engineers and Business users to understand data requirements and ensure the data platform meets their needs.
- Proactively collaborates with the team and Product Manager, actively contributing to discussions, adapting to change and evolving needs, and taking initiative to ensure clear alignment and continuous progress.
Security and Compliance
- Implement security policies to protect sensitive data.
- Ensure compliance with relevant data privacy regulations.
Innovation and Continuous Improvement
- Evaluate and incorporate new technologies, frameworks, and methodologies to improve the platform.
- Actively participate in code reviews, tech discussions, and team learning initiatives.
This is the tech stack you are going to work with
- Spring Boot with Kotlin/Java
- Kubernetes
- Google Cloud Platform (BigQuery, PubSub, GCS, Dataplex)
- Python
- Helm
- And more…
Key success metrics
- Platform adoption by teams (%)
- Reduction in time-to-data-product
- Cost efficiency improvements
- Data quality SLAs
- Ease of use of AI/agentic capabilities
3 reasons why this is (not) for you
Switch to find out
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You don’t like using AI
You prefer to focus only on coding and using AI for development is not your style
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You want to be led by hand
Autonomy and ownership are not for you
-
You like to work by yourself
Transparency and collaboration don't come naturally to you
+
You have an innovative mindset
Constantly seek opportunities to improve yourself, systems and processes and want to apply it (via AI)
+
You communicate like a pro
You are not afraid to be open, ask questions and share your ideas and feedback
+
You are a team player
You thrive in a collaborative environment, value knowledge sharing and supporting each other in the team
In short
You will help build a scalable, governed, and AI-ready data platform that enables hundreds of teams and analysts to create value from data—while shaping the future of analytics at bol.
Perks of having a blue heart
Discover all perks
The culture and the office
Our colleagues work hard to make the daily lives of our customers easier and more fun. But of course, we do this in an inspiring and creative environment!
On and off
At bol we understand like no other that you have to take care of yourself first, then your environment and then bol. In that order. Therefore, everyone at bol receives 29 days of vacation.
Bonus
The bonus is calculated at the end of the year and we always end the year with a fun party!
Interview process
We'll tell you all about applying at bol.
Your application
We’ll review your application with care. We aim to get in touch with you as soon as possible.
First contact
We’ll contact you and walk you through the process and take the first step to set up an interview. And since we’re already talking: feel free to ask any questions you may have.
First date
During the first interview we’ll get to know each other. We want to find out more about you, your work experience and skills.
Your next interview
Before this interview will take place we will ask you to take an online assessment. For some specific jobs we ask you for extra input, for example a business case or a technical assessment. We’ll also discuss the position and the team in depth.
Is this love?
Two interviews are usually enough to see if it’s a match. And if you agree… well, it’s the beautiful beginning of your career at bol.
Any questions?
I'm Sam Surachno, Recruiter at bol. Anything I can help you with regarding the Software engineer – Data Platform vacancy?
Get in touch!
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