Period: 24 August 2026 – 31 December 2026
Project Duration: 14 months
Positions: 4 FTE
Work Arrangement: 100% Remote
 

We are looking for four Data Engineers to join a long-term data engineering project focused on developing and improving modern data pipelines and data warehouse solutions.

In this role, you will work with data coming from Cloudera and MinIO and help move, transform, and organize it across Amazon S3 and Amazon Redshift. You will be involved in building reliable data pipelines, developing warehouse models, and supporting the migration from Cloudera to the MinIO platform.
 

Scope:

• Building and maintaining ELT pipelines from source systems such as Cloudera and MinIO into Amazon S3 and Amazon Redshift.
• Developing and maintaining different data warehouse layers, including Staging, Intermediate, Business View, and Dimensional Models.
• Creating and maintaining fact and dimension tables based on established data models.
• Implementing Transactional, Accumulating Snapshot, and Periodic Snapshot fact tables.
• Implementing Type 1 and Type 2 Slowly Changing Dimensions (SCDs).
• Developing data transformations using dbt and managing pipeline workflows with Apache Airflow.
• Writing and optimizing SQL queries and troubleshooting data-related issues.
• Working with Amazon Redshift for data loading, transformation, and performance optimization.
• Working with data stored in Amazon S3 and Apache Iceberg tables on MinIO.
• Supporting the migration of existing pipelines from Cloudera to MinIO.
• Working closely with data architects, data modelers, and business teams to understand requirements and deliver reliable data solutions.
• Performing data validation and ensuring that pipelines and data models meet quality and business requirements.

Skills:

We are looking for candidates who have strong hands-on experience in data engineering and are comfortable working across cloud, data warehouse, and data transformation technologies.
 

Must-Have Skills

• Strong experience with Amazon S3 and Amazon Redshift.
• Hands-on experience with dbt and Apache Airflow.
• Advanced SQL skills, including experience with: Inner Joins, Self Joins,  Left Joins, Right Joins, Full Outer Joins
• Solid understanding of data warehousing concepts.
• Practical experience working with fact and dimension tables.
• Experience implementing Type 1 and Type 2 Slowly Changing Dimensions.
• Working knowledge of Kimball Dimensional Modeling.
• Hands-on experience with Cloudera, MinIO, and Apache Iceberg.
• Strong experience developing ELT/data pipelines.
• Experience with data migration and modernisation initiatives.
• Good understanding of data quality, transformation, and warehouse design principles.

Good to Have:

• Experience optimizing Amazon Redshift queries and workloads.
• Experience with large-scale data migration from on-premise or legacy platforms to cloud/object-storage environments.
• Experience working in Agile or collaborative data engineering teams.
• Ability to work effectively with technical and business stakeholders.
• Strong problem-solving and troubleshooting skills.

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