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Data Engineer (Marketing & Media Mix Modeling Focus)

Geplaatst 23 mrt. 2025
Delen:
Werkervaring
0 tot 5 jaar
Full-time / part-time
Full-time
Functie
Soort opleiding
Taalvereiste
Engels (Vloeiend)

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Data Engineer (Marketing & Media Mix Modeling Focus)

This position is for a Data Engineer to help lead the implementation of Hunkemoller's Data Mesh on Google Cloud. You’ll work closely with a team of internal engineers to help facilitate and accelerate Hunkemöller’s data transformation initiatives. The right candidate will be excited by the prospect of playing a key role in designing a new data architecture to support next-generation analytics and data initiatives, with a particular focus on Marketing and CRM.

YOUR TASKS

At Hunkemöller, we're on a journey to become a truly data-driven organization. We believe that data and AI are key to unlocking a deeper understanding of our customers and delivering personalized, engaging experiences. This role is critical to that vision, specifically within our Marketing and CRM domains. We're building a cutting-edge Media Mix Modeling (MMM) solution, and this Data Engineer will be instrumental in its development and long-term ownership. This is more than just building pipelines; it's about shaping how we understand and optimize our marketing investments to drive real business impact.

Responsibilities:

  • Build and Maintain Marketing-Focused Data Pipelines: Develop, maintain, and optimize robust and scalable data pipelines using SQL and Google Cloud Platform (GCP) technologies. These pipelines will ingest, transform, and deliver data from a variety of sources, including digital media platforms, CRM systems, and external data providers, ensuring high data quality and reliability.
  • Media Mix Modeling (MMM) Implementation: Play a key role in the development and implementation of our MMM solution. This includes:
    • Building and maintaining Vertex AI pipelines for automated model training, deployment, and monitoring.
    • Implementing data ingestion and transformation processes to support the MMM's data requirements (e.g., handling adstock, saturation, halo effects, and hierarchical data structures).
    • Ensuring the reproducibility and automaticity of the MMM solution, enabling regular (e.g., monthly) updates.
    • Working with data scientists to ensure code quality, containerization, and adherence to software engineering best practices within the MMM project.
  • Data Integration & Transformation: Assemble and transform large, complex datasets (including time-series data, marketing campaign data, and customer transaction data) from diverse sources to meet the specific needs of the MMM and broader marketing analytics.
  • GCP Platform Support: Contribute to the design, implementation, and maintenance of our Google Cloud Platform (GCP) infrastructure, with a focus on automation, data delivery, and scalability, particularly for marketing and CRM data.
  • Data Infrastructure for Marketing: Build and maintain the infrastructure required for optimal extraction, transformation, and loading (ETL/ELT) of marketing and customer data.
  • Data Analysis Tools for Marketing: Develop data analytics tools and contribute to dashboards that leverage our data pipelines to provide actionable insights on marketing campaign performance, customer acquisition, and overall business performance.
  • Collaborate with Stakeholders: Partner closely with Marketing, CRM, Creative, Product, Data Science, and other teams to understand their data needs, resolve technical data issues, and support their data infrastructure requirements. Proactively identify opportunities to leverage data to improve marketing effectiveness.
  • Data Quality and Governance: Implement data quality checks and alerts to ensure the accuracy and reliability of marketing data.

Requirements:

  • Strong SQL Proficiency: Highly proficient in writing complex SQL queries for data manipulation, analysis, and transformation, particularly within a data warehousing environment (e.g., BigQuery).
  • Object-Oriented Programming (OOP): Solid experience with OOP concepts (Python strongly preferred) and applying those principles to data engineering practices.
  • Technical Degree: Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.
  • ETL/ELT Experience: Proven experience working with ETL/ELT tools and Python for building and managing data pipelines. Experience with dbt (data build tool) is a significant plus.
  • GCP Expertise: Hands-on experience with the Google Cloud Platform (GCP), including services like:
    • BigQuery: For data warehousing and large-scale data analysis.
    • Cloud Composer (or Airflow): For orchestrating and scheduling data pipelines.
    • Dataflow (or Apache Beam): For building batch and streaming data processing pipelines.
    • Vertex AI: For building, deploying, and managing machine learning models, specifically experience building Vertex AI Pipelines.
    • Cloud Storage: For storing and managing data.
    • IAM: For managing access and permissions.
  • Data Modeling: Understanding of data modeling principles, including dimensional modeling and data warehousing concepts. Experience with hierarchical data structures is a plus.
  • Marketing Data Understanding: Familiarity with marketing data sources (e.g., Google Analytics 4, social media platforms, CRM systems) and key marketing metrics (e.g., impressions, clicks, reach, frequency, ROI, GRPs).
  • Data Analytics/BI Understanding: Strong familiarity with Data Science and Business Intelligence concepts, particularly as they relate to marketing analytics.
  • Version Control: Experience using Git or other version control systems for collaborative development.
  • English Proficiency: Excellent written and verbal English communication skills, with the ability to clearly explain technical concepts to both technical and non-technical audiences.
  • Agile: Experience working with a team in an agile environment

Bonus Points:

  • Experience with Media Mix Modeling (MMM) or other marketing attribution models.
  • Familiarity with Bayesian modeling techniques.
  • Experience with incrementality testing frameworks.
  • Experience working in the retail industry.

Hunkemöller Culture:

Hunkemöller strives to be a much loved, social & inclusive brand. A place where people love to work, are proud of the brand, and where we create true brand ambassadors. Working in a passionate, energetic, design-led and performance-driven environment where our key customer persona 'Shero' sits at the heart of everything we do. Hunkemöller is certified TOP EMPLOYER of the Netherlands 2025, which underlines our people initiatives and achievements.

Together Tomorrow – Join a Retailer that's on the move to be better for our planet, better for people, better together! From diversity & inclusion, reducing waste, to product care and how we work with our suppliers, our Together Tomorrow initiative reflects what we do and helps drive change across our business. Ready to help us achieving our ambitious goals? Where ever you'll start working with us, if in Stores or our HQs, you can contribute!

Hunkemöller’s mission is to be a much loved, social and inclusive brand - powered by our people. We have over 900 stores in 19 countries and we are growing. Our plans to expand both in Europe and beyond provide exceptional opportunities for those with a passion for retail. Indeed, passion is one our six values: fun, inclusive, passionate, sexy, in-touch and inspiring.
We offer a lot of nice entry level positions for (S)heroes

Retail
Hilversum
Actief in 19 landen
360 medewerkers
30% mannen - 70% vrouwen
Gemiddeld 32 jaar oud