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.
- Hardware & Setup: A high-end laptop and all necessary peripherals to set you up for success.
- Hybrid Flexibility: A balanced work model with 2-3 days on-site in Amsterdam and the rest from home, including a home office budget/setup support.
- Travel Allowance: Full reimbursement for public transport commute or a competitive mileage allowance.
- Impact & Scale: The opportunity to shape global customer data products and governance standards within a world-leading retail enterprise.
- Growth & Learning: Access to training budgets, knowledge-sharing sessions, and modern cloud technologies (GCP, dbt, Databricks).
- Collaborative Culture: An open, inclusive, and international team environment with flat hierarchies and plenty of room for initiative.
- Senior-level experience in Data Engineering, Analytics Engineering, or Data Stewardship.
- Pipeline engineering: Hands-on experience writing production code in dbt or Python on cloud platforms (preferably GCP ).
- Advanced SQL & data modeling: Strong skills in transforming data and building automated tests in dbt .
- Ownership mindset: Proactive problem-solver who thrives in ambiguity and takes the lead.
- Language: Fluent in English .
- Experience with BigQuery , Databricks/PySpark , or Elementary .
- Background working with customer domain data (profiles, transactions, event tracking).
- Knowledge of data governance, metadata management, and data cataloguing.
- Basic dashboarding skills in Looker Studio or Power BI .