(Sr) Data Engineer Retail Media, Measure & Forecast

Advertima; Zürich; On-site; CHF 73,800 - 92,251; Full time

Benefits offered by this job

Flexible Work Policies

Employee Participation Plan

Self-Development Budget

Professional Growth Opportunities

Job summary

A leading technology firm in Zurich is seeking a Data Engineer to build the data backbone of a new media channel. The role involves capturing real-world shopper behavior through distributed edge systems, transforming this data into reliable, scalable products for measurement and decision-making. Ideal candidates should have 5+ years of experience in data engineering and be proficient in Python and Spark. This position offers the chance to shape the future of retail media through innovation and collaboration in a supportive, flexible work environment.

Qualifications

• At least 5 years of experience in data engineering or software development.
• Strong SQL skills with hands-on experience in distributed querying.
• Experience with big data infrastructure and containerized development workflows.

Responsibilities

• Design, develop, and maintain scalable data pipelines using Spark and Python.
• Implement and optimize storage layers for high-performance querying.
• Build, manage, and scale real-time data ingestion pipelines using Kafka.

Skills

Python

Spark

SQL

Kafka

REST APIs

Education

BSc/MSc Degree in Computer Science, Data Engineering

Tools

Hadoop

Docker

AWS

Terraform

Job description

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 anonymised 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, FairPrice, 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.

Job Overview

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 behaviour 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.

Responsibilities

• Design, develop, and maintain scalable data pipelines using Spark and Python to process diverse, high‑volume datasets.
• Implement and optimise 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 visualisations 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 products into core applications.

Qualifications

• BSc/MSc Degree in Computer Science, Data Engineering, or equivalent practical experience.
• At least 5 years of experience in data engineering or software development.
• Proficient in Python with a deep understanding of Spark internals and REST APIs.
• Strong SQL skills with hands‑on experience in distributed querying (Trino) and event‑driven architectures (Kafka, MQTT).
• Experience with big data infrastructure (Hadoop, Iceberg) and containerised development workflows (Docker).
• Good communicator fluent in English (written and spoken).

Ideally, you also have experience in any of the following

• Rust: Interest in or professional experience using Rust for high‑performance data tooling or systems programming.
• Cloud Infrastructure and managed data services (AWS, GCP, Azure).
• Infrastructure as Code (Terraform, Ansible).
• Observability, monitoring, and tracing (Prometheus, Grafana, OpenTelemetry, ELK/Loki).

Benefits

• Innovative Environment: Join a team combining computer vision, IoT, edge computing, and real‑time data pipelines to build enterprise‑grade tech that transforms retail and advertising.
• Global Impact: Collaborate with some of the world’s largest retailers and lead the charge in shaping the future of unified omnichannel Retail Media.
• Professional Growth: As Advertima grows, we’ll create new leadership and specialist roles, giving you a chance to lead those new opportunities.
• Supportive Culture: Be part of a team that values innovation, collaboration, and operational excellence, without the corporate fluff.
• Fast‑paced and International Startup Environment: Work in a high‑growth scale‑up environment with flexibility and scalable processes.
• Flexible Work Policies: Hybrid work environment with the flexibility to balance your personal and professional life.
• Employee Participation Plan: Benefit from our employee participation plan, tying your success to the company’s success.
• Self‑Development Budget: Get your own budget for professional development, learning, and growth.

Culture Fit

• Self‑Management: Take ownership and responsibility without waiting for direction.
• Adaptability and Motivation: Be adaptable, self‑motivated, and enjoy working independently and collaboratively.
• Hands‑On Approach: Roll up your sleeves to solve problems and remove obstacles for yourself and your team.
• Curiosity and Learning: Continuously deepen your understanding of tech, industry, and company direction; ask questions and learn from diverse sources.
• Tech‑Savvy: Comfortable with tools like ClickUp, shared calendars, and AI collaboration tools.
• In‑Person Collaboration: Value face‑to‑face exchanges at the office and team events to build strong relationships.
• Cross‑Functional Teamwork: Comfortable collaborating across teams and engaging in open, direct conversations.
• Feedback Culture: Give and receive direct feedback naturally; it’s how we get better, together.
• Game Changer: Want to shape things, not just manage them; seek opportunities to break the status quo and build something better.

Application

If you are an experienced, resilient Data Engineer who wants to scale the future of global retail media infrastructure, we encourage you to apply.

Please submit your application via this page or send your resume and a cover letter outlining your qualifications and vision for the role to [e-mail].