Senior Data Engineer
what you’ll do.
Design and implement cloud data warehouse and lakehouse architectures using modern data engineering practices
Build and maintain data pipelines that automate ingestion, transformation, and loading of structured and semi-structured data
Develop data automation frameworks to accelerate development and ensure consistency across data platforms
Work with clients to gather technical requirements, assess current architectures, and define implementation strategies for modern data platforms
Implement and optimize ELT/ETL processes, ensuring performance, scalability, and maintainability
Apply data modeling approaches such as Data Vault, dimensional modeling, and hybrid patterns to support automated development
Collaborate with architects and analytics teams to integrate data warehouses with BI platforms, machine learning environments, and other analytical ecosystems
Lead technical workshops, architecture sessions, and design and execute proof-of-concepts and short-term technical consulting engagements
Mentor and guide team members in modern data engineering and data automation practices
Serve as a subject matter expert for leading data engineering and automation platforms, supporting solution design, and helping teams adopt best practices for building scalable, automated data platforms
what you’ll bring.
Bachelor’s degree in IT, applied mathematics, statistics, or a related field, or equivalent practical experience
5+ years of experience in data engineering and data warehousing, ideally within a consulting environment
2+ years of deep experience building cloud-based data platforms using Azure, Snowflake, or similar technologies
Strong experience with data modeling methodologies such as Data Vault, dimensional modeling, or 3NF, combined with a solid understanding of data platform architecture concepts, including metadata management, data governance, and data mesh principles
Experience designing and operating ELT/ETL data pipelines using cloud-native services (Azure/Snowflake), orchestration frameworks (e.g. Airflow), and modern data transformation tools such as dbt
Proven expertise in SQL development and performance optimization
Experience with data warehouse automation platforms or metadata-driven development approaches is highly desirable
Experience working in agile environments and applying DevOps practices to data engineering
A self-starter mindset, able to work independently or collaboratively within multidisciplinary teams
Non-negotiable: strong communication skills in Dutch and English
what’s your score on this list? more than 6 out of 9?
Find out what it’s really like to work for Quest for Knowledge and schedule
a quick sparring session with one of our lead consultants (not recruiters).
apply now!
training guaranteed!
Data and analytics never stand still- and neither do we. To keep up with the pace of change, we make learning a constant part of the journey. We’ve always believed in top-notch training, and over the years we’ve brought in some of the best in the field - like Ralph Kimball, Stephen Few, and Mike Ferguson.
why quest for knowledge.
A truly collaborative culture - you’ll be surrounded by likeminded pros in everything from tech to strategy. We believe in learning together, sharing knowledge, and supporting each other as a team
Room to grow - learning never stops here. From personal development roadmaps to expert-led courses, workshops and certifications, we’ll help you keep building your skills and pushing your potential
Exciting, varied projects – we work with clients across a mix of industries, which means you’ll get to dive into all kinds of interesting projects that keep things dynamic and engaging.
An innovative environment - we’re all about fresh thinking. At Quest for Knowledge, your ideas matter, and we’re here to support creative problem-solving and out-of-the-box thinking every step of the way
Flexibility that fits your life – we’re all about balance. With flexible work arrangements, you can shape your schedule in a way that works for you