Snowflake Data Engineer

• Design and implement data warehouse / Lakehouse architectures on Snowflake in a major cloud (Azure, AWS or GCP).

• Build reliable batch (and where relevant streaming) data pipelines to ingest and transform data into Snowflake.

• Model data for analytics and reporting (star schema, data marts, curated layers).

• Ingest data from various sources (files, APIs, relational databases, SaaS systems) into Snowflake using tools such as Snowpipe, tasks, streams, external stages or external orchestration tools.

• Implement clear, testable and reusable transformation logic using SQL, stored procedures, dbt or similar frameworks.

• Optimize queries, warehouses and storage for performance and cost (clustering, pruning, caching, warehouses sizing).

• Work closely with data analysts, BI developers, analytics engineers and data scientists to make data discoverable, trusted and usable.

• Expose data to BI and analytics tools (e.g. Power BI, Tableau, Looker, Qlik) via well‑designed data models and semantic layers.

• Support advanced analytics / ML workloads that rely on Snowflake as a central data platform.

• Set up and maintain CI/CD pipelines for Snowflake objects and related data engineering code (Azure DevOps, GitHub, GitLab or similar).

• Monitor and troubleshoot data pipelines and Snowflake workloads, ensuring reliability, data quality and efficient resource usage.

• Contribute to best practices, coding standards and reusable components for Snowflake projects within the team.

• Share knowledge and experience within the Data & AI community at adesso (Belgium, Netherlands and beyond) through internal talks, brown‑bag sessions, documentation and PoCs.

• Support pre‑sales activities when needed, by contributing to solution designs, estimations and client workshops around Snowflake‑based architectures.

• In time, coach more junior colleagues who want to grow into strong data engineers on cloud data platforms.

Snowflake, Apache Spark, Azure, Python, PySpark, SQL, Azure Data Lake/Data Factory, AWS, Airflow

You don’t need to tick every box, but you recognize yourself in most of the following:

• Proven hands‑on experience with Snowflake on at least one major cloud provider (Azure, AWS or GCP), including designing and implementing real‑life solutions for clients.

• Strong skills in SQL and experience with data modeling for analytics (dimensional modeling / star schema is a must; data vault or 3NF is a plus).

• Experience building ETL/ELT data pipelines into Snowflake using tools such as dbt, Airflow, Azure Data Factory, AWS Glue, Informatica or similar.

• Understanding of Snowflake‑specific features such as virtual warehouses, time travel, cloning, micro‑partitioning, streams & tasks, and how to use them effectively.

• Good programming skills in Python or another scripting language commonly used in data engineering.

• Familiarity with CI/CD and DevOps practices (Git, Azure DevOps/GitHub/GitLab) for data engineering projects.

• Awareness of data governance, security and compliance in the cloud (roles, access control, masking, encryption, auditing).

• You enjoy working with stakeholders from both business and IT, and you are comfortable clarifying requirements and constraints.

• You can explain complex technical concepts in a clear and pragmatic way, adapted to your audience.

• You are proactive, hands‑on and take ownership of the solutions you build.

• You are comfortable working in multidisciplinary teams and collaborating with colleagues across countries.

• You communicate fluently in French and/or Dutch and are comfortable working in English.

• This position requires current residency and work authorization in Belgium; relocation from other continents cannot be accommodated.

• The opportunity to play a key role in building the Data & AI practice in Belgium, bringing Snowflake expertise into our portfolio alongside Azure, Databricks and Microsoft Fabric.

• Close collaboration with our Dutch Data & AI team and the wider adesso group, giving you access to a broad community of experts, assets and accelerators.

• A personal development plan, training budget and support for Snowflake and cloud certifications.

• Opportunities to grow towards roles such as Senior/Lead Data Engineer, Data Architect or Technical Lead, depending on your ambitions.

• A people‑oriented culture focused on collaboration, trust and entrepreneurship.

• Short decision lines and the possibility to influence our ways of working, technology choices and solution designs.

• A hybrid way of working with a healthy mix of client‑site, office and home.