Senior Data Engineer

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MediaRadar, Inc.

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201 - 500 employés

Fondée en 2007

📣 Marketing

☁️ SaaS

Marketing • Advertising • SaaS

MediaRadar, Inc. est une plateforme de veille publicitaire primée, conçue pour soutenir les ventes médias et la planification publicitaire. Avec plus de 4 millions de marques et des informations de contact complètes, MediaRadar est la solution incontournable pour les vendeurs et acheteurs de médias, fournissant des insights sur les données publicitaires à travers divers formats. La plateforme est largement utilisée dans l'industrie des médias et de la technologie publicitaire pour le démarchage, l'achat média, la planification et l'optimisation des ventes. MediaRadar s'appuie sur des solutions alimentées par l'IA pour délivrer une intelligence publicitaire exploitable, aidant les utilisateurs à prendre des décisions éclairées pour un meilleur mix média et une croissance des revenus.

Description

• We are looking for a highly technical, hands-on Senior Data Engineer to drive the evolution of our data delivery platform while leading a team of data engineers. • This is a player-coach role: you will architect our next-generation data stack, build proofs-of-concept (POCs), and prove out new technologies before we commit to them at scale — and you will also manage and grow a team of engineers who report directly to you. • You will partner closely with engineering leadership to shape the technical direction of our pipelines while staying hands-on in the systems yourself • We are deliberately moving away from a locked-in, vendor-heavy stack toward a flexible, largely open-source architecture that keeps our options open. • We also expect our engineers to work in a modern, AI-assisted way — using AI coding tools and prompt-based workflows to move faster without compromising quality. • You should be energized by evaluating tools, building POCs, and making pragmatic, evidence-based decisions about what we adopt next. • This is a build-and-prove role — you are expected to write code, design schemas, profile queries, and get into the details to understand the "how" and "why" behind every pipeline, while also mentoring your team to do the same.

🎯 Exigences

• Experience: 8+ years in data engineering / ETL, with a strong track record as a hands-on engineer who has architected and built data platforms (Principal-level candidates will bring deeper architectural and cross-team impact). • AI-Assisted Engineering: Hands-on experience using AI coding tools (e.g., GitHub Copilot, Cursor, Claude, or similar) and strong prompt-based development skills, with good judgment about where these tools help and where human review is essential. • Core Databases: Expert-level SQL and RDBMS skills with deep, hands-on experience in SQL Server and Postgres (schema design, performance tuning, complex query optimization, root-cause analysis). • Modern & Open-Source Stack: Hands-on experience with technologies such as ClickHouse, dbt, and open-source data pipeline / orchestration tools (e.g., Airflow, Dagster, or similar), with the judgment to choose the right tool for the job. • Cloud: Strong, hands-on AWS experience is required, as we are standardizing on AWS as we move off Azure Databricks. • POC & Evaluation Mindset: Demonstrated ability to independently prototype, benchmark, and evaluate new technologies and make pragmatic adoption decisions. • Programming: Strong proficiency in Python (or similar) for building and automating data pipelines. • Education: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. • Bonus Points (Nice to Haves) • Domain Expertise: Previous experience in Advertising, Media, or Market Research. • Infrastructure Knowledge: Familiarity with containerization (Docker, Kubernetes) and infrastructure-as-code. • Streaming & Real-Time: Experience with streaming/real-time data technologies (e.g., Kafka).

🏖️ Avantages

• Medical, Dental & Vision Insurance • 401k with Company Match • Flexible PTO • Commuter Benefits • Gym Discounts • Summer Fridays