Data Engineer Omnichannel

Data Engineer (Customer Data Products)

Location

Netherlands, Amsterdam (Onsite work expected)

Background

We need data engineering support in building customer domain data products for a global retail organization, including building pipelines, governance, and data quality management, as well as stakeholder management. This role specifically focuses on data engineering work related to customer classification and unified customer profiles. The role will include driving standards and adoption of data engineering and governance standards together with and in support of other data engineers, data stewards, product owners, and software engineers.

Scope of the Assignment

This role is focused on data engineering but will also require analytics and governance work. We are looking for someone who combines strong technical expertise with stakeholder management skills and the ability to navigate complex conversations.

Responsibilities

Building, improving, and maintaining ingestion and transformation pipelines in SQL and Python (BigQuery, dbt, Databricks), including ad hoc analytics

Managing, reviewing, and improving processes from coding to infrastructure

Creating and implementing data engineering standards from ingestion to transformation, data quality, and data contracts

Reviewing data models, data contracts, and data mappings for alignment with governance standards

Presenting data products, data quality and governance standards, and insights to stakeholders

Collaborating closely with Product, Software Engineering, and Data teams to improve data engineering practices, promote data product principles, and resolve data-related challenges

Requirements

Technical & Analytical Skills

Strong data engineering fundamentals including:

dbt

Python

Production-grade cloud development (GCP preferred)

CI/CD

Infrastructure as Code (IaC)

Containerization

Hands-on experience with:

BigQuery

Databricks / PySpark

Experience with both is strongly preferred

Ability to improve coding, reviewing, and testing practices through smart use of AI

Basic data visualization skills (Data Studio preferred, Power BI is a plus)

Experience with data quality frameworks, testing, and monitoring

Strong understanding of:

Data models

Databases

Data warehousing

Data flows across systems

Experience with customer data (profiles, purchases, interactions) is a strong plus

Experience with customer classifications and unified customer profiles is a strong plus

Knowledge of data governance, metadata management, and data cataloguing is a plus

Communication & Interpersonal Skills

Proactive mindset and ability to thrive in uncertainty

Strong stakeholder management and collaboration skills

Ability to identify and resolve data issues through cross-functional collaboration

Ability to translate business requirements into data products, governance standards, and quality rules

Top 3 Requirements

Strong data engineering fundamentals (dbt, Python, GCP, CI/CD, IaC, Containerization)

Hands-on experience with BigQuery and/or Databricks/PySpark

Proactive attitude and ability to work effectively in ambiguous environments

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