Data Engineer Consultant
Consultant role designing, building, and optimizing cloud data platforms for clients across industries — end-to-end pipelines, ETL/ELT, data modeling, and warehouse/lakehouse solutions using Microsoft Fabric, Azure Data Platform, Databricks, Snowflake, dbt, and Airflow, with SQL and Python, based at the Geneva-area office.
- Compensation
- Not disclosed
- Location
- Meyrin, Switzerland
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Data engineering
- Posted
Skills
Must have
- 3+ years of experience in Data Engineering, Data Warehousing, Analytics Engineering, or a similar role
- Strong understanding of ETL/ELT processes, data modeling, data integration, and data warehousing or lakehouse architectures
- Hands-on experience with one or more modern data platforms: Microsoft Fabric, Azure Data Platform, Azure Data Factory, Databricks, Snowflake, Synapse Analytics, dbt, Airflow, or similar
- Proficiency in SQL and experience with Python or another programming language commonly used for data engineering
- Experience building and maintaining scalable cloud-based data pipelines and data solutions
- Strong analytical, communication, and stakeholder management skills; ability to work directly with clients and business teams
- Fluency in French and English
Nice to have
- Experience with DataOps, CI/CD, infrastructure as code, and cloud-native deployment practices
- Certifications in Microsoft Azure, Microsoft Fabric, Databricks, Snowflake, or other cloud data technologies
Full description
The team, position & mission:
We help clients transform data into a strategic asset by designing, building, and optimizing modern cloud data platforms. Working alongside data architects, analysts, cloud engineers, and business stakeholders, we deliver scalable solutions that support business intelligence, advanced analytics, reporting, and AI-driven initiatives.
As a Data Engineer Consultant, you will work on a variety of client projects across industries, helping organizations build reliable, secure, and high-performing data ecosystems. Depending on the project, you may work with technologies such as Microsoft Fabric, Azure Data Platform, Azure Data Factory, Databricks, Snowflake, Synapse Analytics, dbt, and Airflow to deliver modern data warehouse and lakehouse solutions.
By joining us in this position, you will contribute to the design and implementation of end-to-end data solutions, from data ingestion and transformation to modeling and consumption. You will have the opportunity to continuously develop your expertise, work with leading cloud technologies, and help clients unlock value from their data.
We value people who are proactive on every level, deliver exceptional results, work well with others, and make a clear impact on our clients and our business. If you love collaborating, learning, sharing your expertise, and being recognized for your achievements, you'll fit right in with our team.
Your key areas of responsibility as Data Engineer Consultant:
- Design, build, and maintain scalable data pipelines, data warehouses, lakehouses, and cloud-based data platforms.
- Develop and optimize ETL/ELT processes to ingest, transform, and deliver data from a wide range of sources.
- Create and maintain data models that support analytics, reporting, business intelligence, and AI use cases.
- Collaborate with business stakeholders, data analysts, and solution architects to translate requirements into robust technical solutions.
- Ensure data quality, governance, security, and compliance across data platforms and workflows.
- Monitor, troubleshoot, and optimize data pipeline performance, reliability, and scalability.
- Contribute to automation, testing, CI/CD implementation, and engineering best practices across data projects.
As an ideal candidate you have:
- 3+ years of experience in Data Engineering, Data Warehousing, Analytics Engineering, or a similar role.
- Strong understanding of ETL/ELT processes, data modeling, data integration, and data warehousing or lakehouse architectures.
- Hands-on experience with one or more modern data platforms, including .