Engineering Consulting⌗

I help companies design, modernize and scale data platforms, cloud infrastructure and engineering organizations.

My work ranges from small hands-on infrastructure projects to establishing complete technical platforms and building the teams that can own and evolve them afterwards.

Over the last 14+ years, I have worked across startups, scale-ups and enterprise environments, taking systems from early prototypes to production platforms used across entire engineering organizations.

Typical engagements⌗

Platform Architecture⌗

Designing technical platforms that engineering teams can successfully build upon.

Typical areas include:

  • Data platforms
  • Event-driven architectures
  • Streaming systems
  • Cloud-native infrastructure
  • Internal developer platforms
  • AI and ML infrastructure
  • Distributed backend systems

Infrastructure & Cloud⌗

Building production-ready infrastructure with a strong focus on automation, reliability and maintainability.

Typical work includes:

  • AWS architecture
  • Kubernetes
  • Terraform / OpenTofu
  • CI/CD
  • Networking
  • Observability
  • Infrastructure automation
  • Production readiness
  • Cost and performance optimization

Data Engineering⌗

Designing and modernizing data systems from ingestion to analytics and machine learning.

Typical technologies and areas include:

  • Apache Kafka
  • Kafka Streams
  • Kafka Connect
  • Confluent Cloud
  • Databricks
  • Apache Spark
  • Airflow
  • Dagster
  • Data lakes
  • ETL / ELT modernization
  • Real-time processing
  • Analytics infrastructure

Technical Leadership⌗

Sometimes the main challenge is not a missing technology, but ownership, structure and engineering practices.

I help organizations establish the technical and organizational foundation required to scale engineering teams.

This can include:

  • Technical strategy
  • Architecture reviews
  • Platform ownership models
  • Engineering standards
  • Incident management
  • Hiring
  • Mentoring engineers and team leads
  • Establishing delivery processes
  • Building autonomous engineering teams

From a Small Component to a Complete Platform⌗

Some engagements start with a narrowly scoped technical problem: a service, deployment pipeline, infrastructure component or internal tool.

Others require establishing an entire technical platform.

I work across that whole spectrum:

  • Small infrastructure projects
  • Developer tooling
  • Backend services
  • Cloud environments
  • Distributed systems
  • Streaming infrastructure
  • Data platforms
  • AI infrastructure
  • Engineering processes
  • Team setup and hiring

The goal is not only to deliver software, but to leave behind systems and teams that can continue operating and evolving independently.

Selected Project Areas⌗

Event Tracking & Streaming Platforms⌗

Designing event infrastructure connecting Product Engineering, Analytics and Machine Learning.

Work includes architecture, schema ownership, event delivery, Kafka-based streaming infrastructure and integration with existing data ecosystems.

AI Infrastructure⌗

Building scalable AWS-based infrastructure for production AI workloads.

Recent work included large-scale medical image processing, GPU autoscaling, Kubernetes workloads, Terraform-managed infrastructure and Python services integrating compute infrastructure with AI models.

Data Platforms⌗

Building and modernizing shared platforms for Data Engineering, Analytics and Data Science.

This includes orchestration, infrastructure-as-code, Databricks, Spark workloads, data storage, CI/CD and platform governance.

Kafka & Event-Driven Architecture⌗

Designing and operating Kafka-based platforms for real-time systems.

Experience includes Kafka Streams, Kafka Connect, Confluent Cloud, real-time fraud detection, tracking systems and large-scale event ingestion.

Platform Modernization⌗

Replacing legacy infrastructure with simpler, scalable and maintainable systems.

Examples include:

  • ETL platform migrations
  • Cloud migrations
  • Infrastructure-as-code adoption
  • CI/CD modernization
  • Data lake modernization
  • Operational and observability improvements

Engineering Organization Development⌗

Establishing the teams and practices required to maintain a technical platform long-term.

This can include defining ownership, hiring engineers, introducing engineering standards and creating structures that allow teams to operate independently after the engagement ends.

Open Source⌗

I created kafkus, an interactive tool for working with Apache Kafka.

It was originally built to simplify Kafka onboarding and make event-driven systems easier to explore during development and debugging.

Engagement Models⌗

I typically work as:

  • Interim Engineering Lead
  • Data Engineering Lead
  • Platform Architect
  • Principal / Staff Engineer
  • Interim CTO
  • Technical Advisor

I am comfortable working hands-on as well as taking responsibility for architecture, technical direction and team development.

Working Style⌗

I prefer pragmatic engineering over unnecessary complexity.

That usually means:

  • Understanding the actual business and engineering problem first
  • Building the smallest architecture that solves it well
  • Automating infrastructure and operations
  • Making ownership explicit
  • Creating systems that are understandable by the teams maintaining them
  • Leaving documentation, processes and technical foundations behind

The best consulting engagement is one where the organization no longer needs the consultant to keep the system running.

Contact⌗

If you are building or modernizing a data platform, cloud infrastructure or engineering organization, feel free to get in touch.

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