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# Senior Data Engineer - Databricks & AWS

- **Company:** CGI
- **Location:** Brussel, Belgium
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Amazon Web Services, Amazon S3, JIRA, Microsoft Azure, Big Data, Cloud Database, Computer Programming, Databases, Continuous Integration, Data Cleansing, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Systems, Data Warehousing, Python (Programming Language), Scrum Methodology, Cloud Services, Salesforce.Com, SAP IS-U, SQL Databases, Delivery Pipeline, Apache Spark, Data Lakes, Pyspark, Information Technology, Deployment Automation, Data Analytics, AWS Data Analytics, Data Management, Dataiku, Data Pipelines, Databricks
- **Published:** November 2, 2026
- **Apply:** https://www.adzuna.be/details/5949444137

## About the Role

* 5 to 7 years of professional experience as a Data Engineer or in a comparable data-focused role.
 * Strong hands-on experience with Databricks, preferably within an AWS environment.
 * Solid knowledge of cloud data platforms and AWS services such as S3, Athena, Glue and Redshift.
 * Strong programming skills in Python, Spark or PySpark and SQL.
 * Proven experience designing and optimizing data pipelines and processing large or complex datasets.
 * A good understanding of data-platform management, data lakes and data warehouses.
 * Experience with CI/CD practices and release pipelines, ideally using Azure DevOps.
 * Experience working in Agile environments using Scrum or Kanban.
 * The ability to translate business needs into clear and sustainable technical solutions.
 * Strong communication skills and the ability to explain technical topics to non-technical stakeholders.
 * A collaborative mindset, attention to detail and the flexibility to adapt to evolving technologies and project priorities.

Valuable Additional Experience

 * Dataiku for advanced analytics, data preparation or automation.
 * Data projects within the energy or utilities sector.
 * Integration with platforms such as Salesforce or SAP IS-U.
 * Financial closing or operational reporting processes.
 * Agile delivery tools such as Azure DevOps or Jira.
 * AWS certifications in Cloud Data Engineering, Solution Architecture or Systems Administration.
 * Native-level Dutch or French, combined with good professional communication skills in English.
 * Bachelor's or Master's degree in Information Technology, Computer Science, Data Engineering or a related field, or equivalent professional experience.

## Description

Do you want to do more than simply move data from one system to another?
At CGI, we are looking for an experienced Data Engineer who wants to build the cloud data foundations that organizations can truly rely on. You will design scalable architectures, develop robust data pipelines and transform fragmented data into trusted, reusable sources for analytics and reporting.
Working with Databricks, AWS, Python, Spark and SQL, you will contribute to innovative data solutions that support our clients' transformation and help organizations within the energy sector become more data-driven.

What will you do
You will combine architecture, hands-on engineering and close collaboration with both technical teams and business stakeholders.

 * Designing, implementing and maintaining scalable cloud data architectures using AWS data lakes, databases, data warehouses and Databricks.
 * Building and optimizing automated ETL and ELT pipelines with Python, Spark and SQL.
 * Integrating data from multiple systems and creating unified, reliable and reusable data sources for analytics and reporting.
 * Ensuring data quality, consistency and accuracy throughout the full data lifecycle.
 * Improving the performance, scalability, security and cost-efficiency of data platforms and processing workloads.
 * Working with AWS services such as S3, Athena, Glue and Redshift.
 * Supporting automated deployments and release pipelines through Azure DevOps.
 * Collaborating with business stakeholders to understand their challenges and translate them into effective data solutions.
 * Working closely with architects, analysts, data scientists and development teams to ensure that solutions meet both business and technical expectations.
 * Documenting data architectures, pipelines, processes and technical decisions to facilitate maintenance and knowledge sharing.
 * Promoting strong data-engineering practices across IT and business teams.