Data (Analytics) Engineer

Floryn, a fast-growing Dutch fintech, is seeking a Data (Analytics) Engineer to build and maintain a scalable data foundation. The role involves data modeling in dbt, writing SQL and Python, defining metrics, and automating quality checks. Requires at least two years of relevant experience and strong SQL skills.

HybridFull-timeEntry LevelSQLDbt

Data (Analytics) Engineer

Floryn, a fast-growing Dutch fintech, is seeking a Data (Analytics) Engineer to build and maintain a scalable data foundation. The role involves data modeling in dbt, writing SQL and Python, defining metrics, and automating quality checks. Requires at least two years of relevant experience and strong SQL skills.

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HybridFull-timeEntry LevelSQL

Salary

Not specified

Work Location

's-Hertogenbosch, North Brabant, Netherlands, NL

Work Model

Hybrid working, with regular collaboration at the office in the centre of 's-Hertogenbosch.

Experience Required

2 years

Employment Type

Full-time

Experience Level

At least two years of relevant experience

Core Qualifications

Technical (Must-have)

SQLdbtPythonBigQuerySnowflakeAmazon RedshiftCloud Data WarehouseVersion ControlTestingDocumentationContinuous IntegrationData ModelingSemantic LayerMetabaseHightouchFivetranEstuaryPrefect

Soft Skills

Critical ThinkingCommunicationAutonomyProblem SolvingCollaboration

Key Responsibilities

•Architect, optimise and transform data models in dbt, enabling analysts and the business to work quickly with reliable data.
•Build out the semantic layer so that important metrics are defined once and used consistently across the organisation.
•Automate checks and root-cause analysis around key metrics, making it easier to see what's changing and why.
•Write plenty of SQL and use Python for prototyping, automation and more complex analysis.
•Keep both data and code trustworthy through version control, testing, documentation and continuous integration.
•Work with Analysts, Data Scientists, Developers and Commercial teams to translate business questions into the right metric, dataset or technical solution.
•Build prototypes to test new ideas quickly and improve them together with stakeholders.
•Identify technical bottlenecks yourself and take improvements from initial idea through to implementation.

Data EngineeringAnalyticsFintechdbtSQLPythonData ModelingHybridFull-timeNetherlands