Senior Data Engineer (Product-focused) (m/w/d)

Thryve is a pioneering B2B SaaS company operating at the forefront of health tech infrastructure. We specialize in aggregating billions of patient-generated data points daily, analyzing them in a real-time system to provide cutting-edge insights to our clients. Our clientele includes major health insurance providers across Europe and providers of medical-grade digital therapies.

Founded by three visionaries and supported by venture capital firms specialized in biotech and B2B software, Thryve is driven by a robust, no-nonsense performance culture. We are committed to winning in the health tech space and support our team members by accommodating the life rhythms necessary for maintaining health and high efficiency. We measure outcomes and expect a fervent drive for performance and value at every level of the company.

You'll be part of our AI and Data Analytics team, working at the core of our data platform.

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  Design, build, and operate microservices for real-time data processing

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  Own and evolve our data lake (ClickHouse) and its ingestion pipelines

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  Develop and maintain robust streaming and CDC pipelines (Kafka, Debezium)

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  Improve data quality and reliability in the face of noisy, inconsistent wearable data

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  Collaborate closely with analytics and AI teams to enable high-quality downstream use cases

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  Act as a technical sparring partner for data modeling and pipeline design decisions

Wearable data is fundamentally unreliable:

• Devices fail or behave inconsistently

• Users forget, misuse, or change behavior

• Biological signals vary widely between individuals

You'll build systems that don't just process data — they interpret and stabilize it. Curiosity about how wearables work and data is generated (and not just how it's processed and stored) is therefore a key requirement.

• Strong analytical thinking and a desire to deeply understand data problems

• Solid experience with SQL and data modeling

• Hands-on experience with ClickHouse (or comparable analytical databases)

• Experience building and operating data pipelines (Kafka, CDC, streaming)

• Experience developing microservices in Python for real-time processing

• Experience deploying applications in Kubernetes using ArgoCD and configuring via Helm Charts

• Ability to work independently and take ownership of systems end-to-end (we have a strong "you build it, you own it" culture)

• Experience working with wearable, health, or time-series data

• Interest in biology, physiology, or medical applications

• Experience with statistical analysis or data validation techniques

• A strong sense of data quality and curiosity-driven exploration

• Experience with unstructured data pipelines (NoSQL, S3) and health data standards (HL7/FHIR)

• Familiarity with feature store architectures

• Microservices: Kubernetes, Helm Charts, ArgoCD

• Data Processing: Python, Debezium

• Data Platform: ClickHouse

• Streaming & Messaging: Kafka, RabbitMQ

• Observability: OpenTelemetry, Grafana (Tempo, Loki, Prometheus)