Senior Analytics Engineer: Build the Single Source of Truth

BridgeFund; Amsterdam; Hybrid; EUR 66,000 - 73,000; Full time

Benefits offered by this job

Hybrid model (3 days in office)

25 vacation days + 8% holiday

Remote work from abroad 2 weeks/year

Travel allowance €0.23 per kilometer

€40 Alleo budget per month

BridgeFund Academy

Learning budget €1,500 per year

MacBook workspace

BridgeDay

Company boat The Royal Ted

Sports activities

50% paid lunches

Free snacks

Friday drinks and team events

BridgeFun(d) bar

Job summary

BridgeFund is seeking a Senior Analytics Engineer to own our central data foundation, turning high-level business goals into robust, production-ready data platforms used for analytics, modeling and AI use cases.

You will lead data modeling in Databricks, coordinate with Finance, Product, Platform and AI teams, and champion best practices like CI/CD, data quality checks and unified metrics across the business.

Qualifications

• 5+ years hands-on experience in Data/Analytics Engineering.
• Production-level SQL and Python; CI/CD experience.
• Databricks and PySpark experience preferred.
• Experience with dbt, Kimball, or Databricks modelling.

Responsibilities

• Design, build, and maintain production data models in Databricks (Gold layer).
• Lead requirements sessions with Finance and Product; liaise with Platform and AI teams.
• Resolve live and historical data integration issues across systems.
• Model data from CDC sources to capture audit histories.
• Build automated quality checks, monitoring dashboards, and alerting; standardize naming and Unity Catalog tagging.
• Define company-wide metrics; align definitions across the business.
• Advocate best practices: version control, testing, and CI/CD.

Skills

Data engineering

Analytics engineering

SQL

Python

CI/CD pipelines

Tools

Databricks (PySpark)

dbt

Kimball

Databricks modelling

Job description

BridgeFund is seeking a Senior Analytics Engineer to own our central data foundation, turning high-level business goals into robust, production-ready data platforms used for analytics, modeling and AI use cases.

You will lead data modeling in Databricks, coordinate with Finance, Product, Platform and AI teams, and champion best practices like CI/CD, data quality checks and unified metrics across the business.