Data Engineer / Data Steward

Huxley; Amsterdam; Hybrid; EUR 70,000 - 110,000; Full time

Job summary

Huxley in Amsterdam is seeking a Data Engineer / Analytics Engineer / Data Steward to build customer data products, pipelines, and governance frameworks. You will manage data quality, metadata, and stakeholder enablement while collaborating with product and engineering teams.

The role sits at the intersection of Data Engineering, Analytics Engineering, and Data Stewardship, valuing candidates with deep expertise in one area and solid foundation in others. 2-3 days onsite per week in Amsterdam.

Qualifications

• Experience building pipelines with dbt or Python.
• Production-grade solutions on cloud platforms (GCP preferred).
• Hands-on BigQuery and PySpark/Databricks experience.
• Strong SQL skills and dbt modelling.
• Familiarity with data quality frameworks and governance concepts.
• Knowledge of data models, warehousing, and data flows.
• Basic data visualization using Data Studio or Power BI.

Responsibilities

• Build, improve, and maintain ingestion and transformation pipelines using SQL and Python.
• Perform ad hoc analytics when required.
• Define and maintain data quality rules, tests, and dashboards using dbt and Elementary.
• Lead root-cause analysis for data quality issues and drive corrective actions.
• Maintain business definitions, harmonisation rules, and metadata across datasets.
• Review data models, data contracts, and data mappings for governance alignment.
• Present data product, governance, and data quality insights to stakeholders.
• Collaborate closely with data engineers, data stewards, software engineers, and product teams.

Skills

Data engineering fundamentals

dbt

Python

SQL

Cloud platforms (GCP)

BigQuery

Databricks

Data governance

Metadata management

Data quality testing

Data models & warehousing

Data visualization basics

Tools

dbt

Power BI

Data Studio

BigQuery

Databricks

Miro

Job description

Data Engineer / Analytics Engineer / Data Steward

Location: Amsterdam (2-3 days onsite per week)

Background

We need data engineering and governance stewardship support to build customer domain data products, including building pipelines, data quality management, governance frameworks, metadata management, and stakeholder enablement. The role involves driving adoption of data governance standards, ensuring discoverability and clear data definitions, and collaborating with product and engineering teams to improve data reliability and usability.

Scope of the Assignment

This role sits at the intersection of Data Engineering, Analytics Engineering, and Data Stewardship. We are looking for a professional who brings expertise across all three areas, although candidates with deep expertise in one area and a solid foundation in the others will also be considered.

Responsibilities

• Build, improve, and maintain ingestion and transformation pipelines using SQL and Python
• Perform ad hoc analytics when required
• Define and maintain data quality rules, tests, and dashboards using dbt and Elementary
• Lead root-cause analysis for data quality issues and drive corrective actions
• Maintain business definitions, harmonisation rules, and metadata across datasets
• Review data models, data contracts, and data mappings for governance alignment
• Present data product, governance, and data quality insights to stakeholders
• Collaborate closely with data engineers, data stewards, software engineers, and product teams

Required Skills & Experience

Technical & Analytical Skills

• Strong data engineering fundamentals, including building pipelines in dbt or Python
• Experience developing production-grade solutions on cloud platforms (GCP preferred)
• Hands-on experience with BigQuery and/or PySpark/Databricks
• Strong SQL skills
• Experience with dbt modelling and data quality testing
• Familiarity with data quality frameworks and methodologies
• Knowledge of data models, databases, data warehousing, and system data flows
• Experience with customer data (profiles, purchase events, interaction data) is highly desirable
• Understanding of data governance frameworks, metadata management, and data cataloguing practices is a plus
• Basic data visualisation experience (Data Studio preferred, Power BI advantageous)

Communication & Stakeholder Management

• Strong collaboration skills across business and technical stakeholders
• Ability to present findings through dashboards, Miro, and similar tools
• Strong problem-solving skills with a focus on ownership and resolution
• Ability to translate business requirements into data products and governance standards
• Proactive mindset and comfort working within ambiguity

Top 3 Requirements

• Data engineering fundamentals, including pipelines in dbt or Python and cloud-based development (GCP preferred)
• Strong SQL skills with dbt modelling and data quality testing experience
• Proactive mindset with the ability to drive initiatives in an evolving environment