Senior Data Platform Engineer (dbt, Databricks, Apache Spark, Python)
Summary
Senior Data Platform Engineer at Albert Heijn owning and modernizing the data platform behind its retail media SaaS for brands across Europe. Day to day: building scalable batch/streaming pipelines with dbt, Databricks, Apache Spark, SQL and Python, enforcing data quality, and mentoring engineers. Netherlands-based, salary up to €105K.
In this role you will own and advance a data platform powering a retail media SaaS used by multiple brands across Europe. You will drive data engineering best practices, modernize pipelines with dbt and Databricks, and enable self-service data capabilities for cross-brand teams. You’ll tackle scalable batch and streaming data, ensure data quality and observability, and collaborate across engineers to raise engineering quality. This is a mission-driven opportunity to shape data platforms for a fast-growing ad-tech ecosystem.
Arbeidsvoorwaarden / Benefits- Annual salary up to 105K including holiday allowance and flexible bonus
- Minimum 20 days paid vacation (option to add 12.5 more)
- Flexible working hours
- AH Tech Academy training curriculum
- Pension plan with enhanced employer contribution
- Travel allowance or NS-business card
- Migrate and design data pipelines on a modern dbt-based platform
- Develop and evolve scalable batch and streaming data systems processing millions of records
- Embed test automation and data quality standards into delivery workflows
- Guard data models and data integrity for downstream consumers
- Build self-service data models to empower other teams
- Improve reliability, performance, and cost-efficiency of the data platform
- Coach and mentor engineers through reviews, standards, and knowledge sharing
- Lead technical discussions and help teams evaluate architectural trade-offs
- Partner with platform engineers and architects to shape the platform’s direction
- 5+ years of data engineering experience
- Extensive hands-on dbt experience (data modeling, testing, incremental processing)
- Strong Databricks and Apache Spark in production
- Strong SQL and Python development
- Experience designing and operating batch and streaming data pipelines
- Experience with lakehouse/medallion architectures
- Experience optimizing performance, reliability, and cloud costs at scale
- Experience with Terraform and IaC practices
- Mentoring and coaching engineers
- Proactive ownership and initiative
- Strong communication and stakeholder management
- dbt data modeling, testing, incremental processing
- Databricks
- Apache Spark