Sr Data Engineer Retail Media, Measure & Forecast

About Advertima Vision

Advertima is building the missing infrastructure that brings the power of digital advertising to the physical world.

Today, most advertising inside physical retail stores still operates like the internet did twenty years ago: static screens, no audience intelligence, and almost no measurable performance. Meanwhile, online advertising evolved into a trillion-dollar ecosystem powered by real-time data, automation, and programmatic infrastructure.

We are changing that.

Advertima has built the technology that transforms physical retail environments into real-time, data-driven media channels. Using computer vision, edge computing, and distributed AI systems, we translate physical shoppers into anonymized digital audiences that can be measured, targeted, and activated in real time.

This is not a theoretical vision or an incremental improvement. It is the creation of a completely new global technology standard.

Global retail leaders such as Walmart, Carrefour, Fair Price, SPAR, and EDEKA are deploying our technology across thousands of stores. Together, we are defining the global standard for In-store Retail Media.

But building the infrastructure is only one part of the problem. The next major challenge is turning real-world, imperfect, high-volume sensor data into reliable measurement and forecasting systems. In online advertising, this layer defines how performance is measured, how budgets are allocated, and how value is created.

In physical retail, this layer does not exist yet. We are building it.

At the same time, everything we build follows a strict privacy-by-design philosophy. Our systems operate without processing and storing personal data or images, while still enabling the audience intelligence required for real-time performance media. This approach, rooted in Switzerland’s strong privacy culture, has become one of the key reasons global retailers trust Advertima to power their next-generation Retail Media infrastructure.

Solving this combination of distributed systems, edge computing, AI inference, privacy-preserving data processing, and global-scale reliability is a hard engineering problem. That is exactly why we are building our core engineering team in Zurich.

If you enjoy working on complex real-world systems, pushing the boundaries of edge and cloud infrastructure, and helping define a new global technology category, Advertima offers a rare opportunity.

We are looking for a Data Engineer to help build the data backbone of a completely new media channel. Our platform captures real-world shopper behavior through distributed edge systems and turns it into high-volume, real-time data streams. Your job is to transform this raw, imperfect data into reliable, scalable data products that power measurement, forecasting, and decision-making across the Retail Media ecosystem.

This is not a typical data platform. You will work on systems that:

• process continuous data streams from thousands of physical touchpoints
• turn noisy, real-world signals into structured, trustworthy datasets
• power measurement, attribution, and forecasting models
• enable real-time and batch decision-making across the adtech ecosystem

Technically, this means building and operating a modern data stack combining real-time streaming, large-scale batch processing, and lakehouse architectures — bridging edge-generated data with cloud-based analytics and applications.

You will join a team that values pragmatic engineering, clean abstractions, and systems that actually work in production under real-world conditions.

• Design, develop, and maintain scalable data pipelines using Spark and Python to process diverse, high-volume datasets.
• Implement and optimize storage layers (Apache Iceberg, Avro, Hadoop) and cloud-native object stores (S3/GCS) for high-performance querying via Trino.
• Build, manage, and scale real-time data ingestion pipelines using Kafka and MQTT.
• Create REST APIs, build intuitive visualizations with Apache Superset, and maintain data contracts for external and internal sharing.
• Collaborate closely with Data Scientists and Backend Engineers to turn raw data into features and integrate data…