Description

I’m a senior backend and data engineer with deep experience building production-grade microservices and modern data platforms for high-scale, data-intensive businesses. I specialize in designing systems that are reliable, observable, and easy to evolve as teams and requirements grow.

On the backend side, I work extensively with:

Designing and implementing microservices and APIs (Python, JVM-based stacks)
Event-driven and asynchronous systems using Kafka, queues, and streaming architectures
Service-to-service communication
Performance optimization, fault tolerance
Production readiness: logging, metrics, tracing, and alerting

On the data engineering side, I help teams design and operate robust data platforms:

End-to-end data pipelines (batch and streaming) from ingestion to analytics
Data lake / lakehouse architectures using open table formats (Iceberg, Delta Lake, Hudi)
Data modeling for analytics, metrics layers, and downstream consumption
Orchestration and workflow design (Airflow, custom schedulers)
Data quality, observability, and governance built into pipelines

I have strong hands-on experience with cloud-native systems (AWS-centric), including:

Infrastructure design with scalability and cost efficiency in mind
CI/CD pipelines, automated testing, and deployment workflows
Operating systems in production with a focus on reliability

I’m particularly effective in engagements where:

The system is already in production and needs hardening, refactoring, or scaling
Data platforms need to move from ad-hoc pipelines to well-architected, maintainable systems
Engineering teams need help with architecture decisions, not just implementation

I work well with cross-functional teams, can operate independently, and focus on delivering solutions that are pragmatic, well-documented, and production-ready.

Languages

English
Native or bilingual

Workplace preferences

Remote only

Primarily works remotely

Ratepay
Principal Software Engineer
December 2025 - Today (6 months)
Germany
Own the end-to-end architecture and strategy for Ratepay's engineering, analytics and reporting platform, spanning Microservices, AWS, Kafka, Snowflake, and downstream BI and regulatory systems. Lead the redesign of data ingestion and transformation pipelines (streaming + batch), improving reliability, scalability, and cost efficiency across high-volume financial and transactional data. Drive standardization of data modeling, orchestration, and transformation practices (dbt, Snowflake tasks, Airflow), reducing fragmentation and operational overhead across teams. Partner closely with Risk, Finance, AML, and Product domains to deliver compliant, auditable, and business-critical data products supporting regulatory reporting and decision-making. Provide technical leadership and mentorship to senior engineers, setting engineering standards, reviewing designs, and influencing long-term platform and tooling decisions.
Data integration (ETL, ELT and data warehousing) Microservices Architecture Apache Kafka SQL Python
HelloFresh
Senior/Staff Software Engineer - Data
E-COMMERCE
June 2024 - December 2025 (1 year and 6 months)
Germany
Enhance and maintain a critical high throughput service that manages customers preferences across all channels(Python, Kafka, AWS RDS Postgres) Primary contributor to the design and architecture of a mobile, data and backend initiative to unblock mobile reachable audience for the company (CVA impact > €24 mio) Enhance and maintain a critical high throughput(>10k rps) analytics service driving events analytics for mobile communication channels (Python, Kafka, AWS RDS Postgres) Maintain a medallion data lake on Amazon S3 using the Glue data catalog and Databricks Photon as the query engine, pipelines written in Spark and deployed on AWS EMR. Led the design and implementation of data contracts for all critical data pipelines and assets for the communications domain
Apache Spark Apache Kafka Python SQL Database Management (e.g., SQL, NoSQL)
New Work SE
Senior Software Engineer - Data and ML Platform
DIGITAL AND IT
March 2022 - June 2024 (2 years and 3 months)
Berlin, Germany
Worked on a company-wide Machine learning platform solution deployed on AWS (>70% adoption in the company). Personal Contributions include a core library to access training data agnostic of the query engine, model deployment and model versioning(registry). Led the deployment of a company-wide data lake solution on AWS. Included a solution to migrate data from on-premise HDFS clusters to S3(GitOps, Glue, Spark, EMR, Hudi, Kafka) Maintained multiple backend Scala services like Recent searches(Akka, Kafka, Cassandra) and a legacy Recommendations service(Akka, Shapeless, ElasticSearch). Data pipelines leveraging Kafka streams, Kafka connect, Akka streams, Spark and Oozie workflows Led the deployment of a Vector database platform(Qdrant) on AWS EKS to enable generative AI applications (Terraform, Terragrunt, GitOps) Sole contributor to a high performance service for nearest neighbour searches on the Vector database. Implemented caching and basic auth on top ofthe existing DB endpoint (Rust, AWS EKS, Redis)
Apache Kafka Apache Spark SQL Database Management (e.g., SQL, NoSQL) Scala