Data & Analytics Engineer

YoungCapital NEXT; Netherlands; On-site; EUR 85,000 - 120,000; Full time

Job summary

YoungCapital NEXT is seeking a Senior Consultant at the intersection of Data Engineering, Analytics Engineering, and Data Stewardship to build and scale Customer Domain Data Products across a global retail enterprise. You will develop data pipelines, define data quality rules, and implement governance and metadata frameworks to ensure customer data is reliable and discoverable.

Ideally you bring a blend of data engineering and data stewardship, but strong specialists in one area with solid

Qualifications

• Experience building data pipelines and data products with strong data governance.
• Proficiency in SQL, Python and dbt; familiarity with data quality frameworks.
• Ability to translate business requirements into trusted data products.

Responsibilities

• Build, optimize, and maintain scalable ingestion and transformation pipelines using SQL, Python, and dbt.
• Define and maintain data quality rules, automated tests, and monitoring dashboards (e.g., using dbt / Elementary).
• Maintain business definitions, harmonization rules, metadata, and cataloguing across datasets.
• Translate business requirements into trusted data products; present metrics, data quality health, and governance insights to stakeholders.
• Partner with data engineers, data stewards, software engineers, and product owners to improve end-to-end data usability and reliability.

Skills

Data engineering

Data stewardship

Analytics engineering

SQL

Python

Data quality

Governance

Metadata management

Stakeholder communication

Tools

dbt

Elementary

Job description

We are seeking a Senior Consultant at the intersection of Data Engineering, Analytics Engineering, and Data Stewardship for a leading global retail enterprise. In this role, you will play a central part in building and scaling Customer Domain Data Products across the international organization. You will help build robust data pipelines, establish automated data quality standards, implement governance and metadata frameworks, and ensure customer data across the company is reliable, well-documented, and readily discoverable. While the ideal candidate brings a blend of data engineering and data stewardship, applications are also very welcome from strong specialists in one area who have solid fundamentals in the other.

Scope & Key Responsibilities

• Pipeline Development & Maintenance: Build, optimize, and maintain scalable ingestion and transformation pipelines using SQL, Python, and dbt, while supporting ad-hoc analytics needs.
• Data Quality & Reliability: Define and maintain data quality rules, automated tests, and monitoring dashboards (e.g., using dbt / Elementary). Lead root-cause analyses for data anomalies and follow up on corrective actions.
• Data Stewardship & Governance: Maintain business definitions, harmonization rules, metadata, and cataloguing across datasets. Review data models, data contracts, and schema mappings to ensure alignment with governance standards.
• Stakeholder Enablement & Reporting: Translate business requirements into trusted data products; present product metrics, data quality health, and governance insights to both technical and non-technical stakeholders.
• Cross-Functional Collaboration: Partner closely with data engineers, data stewards, software engineering, and product owners to improve end-to-end data usability and reliability.