Senior Software Engineer (m / w / d)

We are seeking an expert in modern data architecture and cloud solutions to develop cloud-based data platform solution accelerators for high-priority use cases, with a strong focus on connected mobility and fleet management. The role focuses on building reusable, production-grade codebases that can be rapidly adapted for customer pilots, accelerating both sales cycles and implementation efforts.

Location : Berlin

Work Schedule : 40 hours per week

Key Responsibilities

Solution Development :

Act as a hands-on developer to build production-ready solution accelerators with reusable, modular, and adaptable codebases.

Performance Optimization :

Design and implement low-latency data pipelines, including the transition from micro-batch processing to streaming architectures using SQL-based processing frameworks and native streaming ingestion services.

Documentation & Assets :

Deliver enablement assets such as GitHub repositories, architecture diagrams, and technical documentation to support field teams and partners (e.g., system integrators) in implementations and customer pilots.

Requirements

Real-Time / Streaming Ingestion :

Hands-on experience with native streaming ingestion services for high-volume, low-latency telematics data.

Application Hosting :

Experience using managed container services within a cloud data platform to containerize and deploy services, including cost-effective open-source routing engines.

Visualization :

Strong expertise in building front-end applications and dashboards using modern data app frameworks (e.g., Streamlit) to deliver actionable operational insights (KPIs, alerts, heatmaps).

Data Science & Machine Learning :

Working knowledge of applying machine learning models for analytical and predictive use cases on large-scale datasets.

Advanced Analytics (Nice to Have) :

Experience with time-series analytics and geospatial capabilities, including H3 hexagonal indexing.

Preferred Industry Experience

Experience with fleet and IoT intelligence use cases is a strong plus, including :

Predictive Maintenance :

Integrating IoT sensor data (e.g., diagnostic trouble codes, voltage, temperature) to predict asset failures and trigger automated work orders.

Fleet Efficiency & Optimization :

Route optimization and deviation detection

Inbound logistics visibility for just-in-time production

Idling reduction using near real-time vehicle telemetry

IoT Operations Intelligence :

Building reusable architectures that address shared challenges across moving and stationary assets, such as time-to-action and predictive maintenance.