Data platforms for decisions and operations.

Winble helps organisations design and build modern data platforms and the architecture around them, so data can support both decisions and everyday work.

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Enterprise architecture built to last
Data & AI from platform to decision
Development of systems and data flows

Services

Support from the first architecture decisions through to development with your team.

Data platform architecture

EngagementA defined architecture engagement or ongoing architecture support.

When data sits in many systems, you need a shared direction for how to collect, share and use it. Marcus designs data platform architecture around your business needs and maps a path from the current solution to the next step.

Mapping of data sources, needs and dependencies
Target architecture with platform choices and data models
Phased implementation and modernisation plan

Typical outcome: A shared direction for the data platform and a basis for prioritisation and implementation.

Data engineering and pipelines

EngagementPart-time or full-time development engagements with your team.

Analytics and operational services need connected data that can be traced to its source. Marcus builds integrations, pipelines and data models, from ingestion to analytics and APIs. Where needed, the data flow can also support ML models, for example for valuation or forecasting.

Integrations and pipelines from internal and external sources
Data warehouses and tabular models for analytics
Data access through reports and APIs

Typical outcome: Connected data flows that give teams a useful foundation for analytics and services.

Enterprise and solution architecture

EngagementArchitecture engagements or recurring support as an architect and tech lead.

When a monolith needs to change, the business, systems and teams need to move in the same direction. Marcus develops target and transition architectures using domain-driven design and data mesh, including responsibility and access when sharing data. Working prototypes make architecture choices tangible for development teams.

Domain boundaries and target architecture based on the business
Transition architectures for gradual change
Prototypes for data products, integration and access

Typical outcome: A practical direction for change with clearer system boundaries and responsibilities.

Advisory and team leadership

EngagementAdvice, workshops or ongoing part-time team support.

Technical choices and dependencies between teams can make progress difficult. Marcus helps teams and product owners clarify the options, plan the work and follow up on improvements. He combines technical advice with experience as a Scrum Master and team coach.

Review of architecture and technical choices
Joint planning and dependency management
Coaching and follow-up on team improvements

Typical outcome: Clearer priorities and a shared way of working to move development forward.

Selected experience

Examples from Marcus's work in the automotive industry and automotive retail. The organisations are described without names.

Modernising an enterprise data warehouse

Software company in automotive retail

Challenge: Data from many internal and external sources needed to be brought together as a shared basis for analytics.
Solution: Together with a colleague, Marcus led the development of a new enterprise data warehouse and tabular analytics models that consolidated the sources.
Result: The data warehouse and analytics models became a shared foundation for advanced analytics and visualisation.
Technology and architecture: SQL
DAX
Tabular Model

ML-based car valuation through an API

Software company in automotive retail

Challenge: Historical sales data needed to become useful for estimating the value of an individual car.
Solution: Marcus developed an ML model using 20 years of car sales history. The model used the car's characteristics and was made available through a vehicle API.
Result: The service could provide an estimated sales value based on the car's registration number.
Technology and architecture: SQL
Python
C#

Domain-driven architecture and secure data sharing

Global premium car manufacturer

Challenge: A complex monolith needed a gradual path towards domain-based systems and data sharing with clear ownership.
Solution: Marcus developed target and transition architectures and a data mesh strategy with federated security. Working prototypes demonstrated data products and access control where data owners managed access.
Result: Teams gained a concrete direction and working examples to explore ahead of further development.
Technology and architecture: Domain-Driven Design
Data mesh
C#
SQL
OAuth 2.0

Micro frontends in a working prototype

Global premium car manufacturer

Challenge: Development teams needed to understand how a larger interface could be divided as part of the shift from a monolith to domain architecture.
Solution: Marcus built a prototype in which independent frontend modules together formed a coherent web application.
Result: Teams could run the solution and read the code to see how independent parts can provide a shared user experience.
Technology and architecture: C#
React
TypeScript

About Marcus

Senior data and enterprise architect

Marcus Wittenstam has worked with data since 2017, from BI development and consulting engagements to data platforms and enterprise architecture.

In automotive retail, he has modernised data warehouses, developed an ML-based car valuation service and worked as a Scrum Master and team coach.

Since 2022, he has worked as an Architect / Staff Engineer at a global vehicle manufacturer, focusing on domain-driven architecture, data mesh and secure data sharing.

Through Winble, he combines strategic choices with practical development and support for the teams putting them into practice.

Architect
Tech lead
Hands-on developer

Read Marcus's CV Marcus on LinkedIn

Technology and ways of working

Tools and architecture principles from Marcus's work. Choices for each engagement are based on your needs and existing environment.

Platforms and cloud

Azure
Fabric
Synapse
Kubernetes
Foundry

Data and analytics

Power BI
DAX
Tabular Model
SQL

Languages

Python
C#
TypeScript

Ways of working and architecture

Domain-Driven Design
Data mesh
Target and transition architecture
Scrum
Team coaching
Git
GitHub

Book a conversation about your project

Tell us what you want to do with your data and where you need support. An initial 30-minute conversation gives us the opportunity to discuss needs, scope and working together.

Engagements can be remote or based in Göteborg, part-time or full-time. We agree the scope and start date together.

Book 30 minutes marcus.wittenstam@winble.se Marcus on LinkedIn