Analytics Engineer — Shape Centralized Data & BI (Fintech)

Harnham; Amsterdam; On-site; EUR 60,000 - 90,000; Full time

Job summary

Harnham, a technology-led financial services firm in Amsterdam, is expanding its central data function to standardize data modelling, analytics and reporting. The Analytics Engineering team designs scalable data models using SQL and dbt, and uses Python to support data transformation workflows.

You will bridge data engineering and analytics, improve data quality and accessibility across a high-volume platform, and work with stakeholders to translate analytical requirements into robust data

Qualifications

• Strong commercial experience as Analytics Engineer or similar data role.
• Advanced SQL and data modelling capabilities.
• Hands-on dbt experience.
• Strong Python skills in data/analytics environments.
• Experience building reliable datasets for downstream analytics and BI.
• Comfortable bridging data engineering and analytics teams.
• Fintech/financial services or high-volume tech experience beneficial.

Responsibilities

• Design, develop and maintain scalable data models using SQL and dbt.
• Use Python to support data transformations and analytics engineering workflows.
• Bridge the gap between data engineering and analytics teams.
• Improve data quality, consistency and accessibility across the organisation.
• Contribute to central data modelling standards within a centralised data function.
• Work with stakeholders to translate analytical requirements into robust data solutions.
• Support analytics and BI use cases across a high-volume technology environment.

Skills

Advanced SQL

dbt

Python

Data modelling

Data pipelines

Cross-functional liaison

Fintech domain experience

Job description

Harnham, a technology-led financial services firm in Amsterdam, is expanding its central data function to standardize data modelling, analytics and reporting. The Analytics Engineering team designs scalable data models using SQL and dbt, and uses Python to support data transformation workflows.

You will bridge data engineering and analytics, improve data quality and accessibility across a high-volume platform, and work with stakeholders to translate analytical requirements into robust data