Data Engineer Omnichannel

Huxley; Amsterdam; On-site; EUR 75,000 - 110,000; Full time

Job summary

Huxley is seeking a Data Engineer (Customer Data Products) in Amsterdam with onsite work. You will build and maintain ingestion/transformation pipelines using SQL and Python in BigQuery, dbt, and Databricks, while driving data governance and quality standards.

Collaboration with Product and Data teams will align data models and contracts with governance goals. You will work on customer classifications and unified customer profiles, delivering data products and insights to stakeholders and

Qualifications

• Strong data engineering fundamentals including dbt and Python.
• Production-grade cloud development with GCP is preferred.
• Experience with CI/CD, IaC, and containerization.

Responsibilities

• Building, improving, and maintaining ingestion and transformation pipelines in SQL and Python (BigQuery, dbt, Databricks).
• 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 governance alignment.
• Presenting data products, data quality and governance standards, and insights to stakeholders.
• Collaborating with Product, Software Engineering, and Data teams to improve data engineering practices.

Skills

dbt

Python

GCP

CI/CD

IaC

Containerization

Tools

BigQuery

Databricks

PySpark

Job description

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