Data Engineer: Cloud & Data Warehouse Architect

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

Benefits offered by this job

Hybrid working arrangements

Training programs & certifications

Career growth opportunities

Job summary

OBSS in Amsterdam seeks a Data Engineer to drive the integration of a new retail banking platform into our enterprise data landscape. You will connect cloud data lakes, APIs and real-time streams to feed our data warehouse and data marts.

You will lead end-to-end integration by defining source-to-target mappings, designing scalable data models, ensuring data quality and lineage, and partnering with cross-functional stakeholders to establish clear data definitions and governance.

Qualifications

• Strong SQL, data modelling, ETL and data warehouse experience.
• Experience with data quality, lineage governance and stakeholder requirements.
• Banking or financial-services experience is strongly preferred.
• Familiarity with AWS data lakes or streaming concepts.

Responsibilities

• Consume data from cloud-based data lakes, APIs and data streams and load it into the enterprise data warehouse.
• Analyse source data and define source-to-target mappings and transformation rules.
• Design and maintain logical and physical data models.
• Integrate new data into existing data warehouse structures and data marts.
• Work with business stakeholders to define data meaning, ownership and usage.
• Define and implement data-quality checks and reconciliation controls.
• Produce clear technical and functional documentation for data flows, models and transformations.

Skills

SQL

Data modelling

ETL / Data integration

Data warehouse

Data quality & governance

Stakeholder engagement

Tools

AWS

Job description

OBSS in Amsterdam seeks a Data Engineer to drive the integration of a new retail banking platform into our enterprise data landscape. You will connect cloud data lakes, APIs and real-time streams to feed our data warehouse and data marts.

You will lead end-to-end integration by defining source-to-target mappings, designing scalable data models, ensuring data quality and lineage, and partnering with cross-functional stakeholders to establish clear data definitions and governance.