Help design, build and continuously improve the clients online platform.
Research, suggest and implement new technology solutions following best practices/standards.
Take responsibility for the resiliency and availability of different products.
Be a productive member of the team.
Requirements
5+ years of professional data engineering experience working with Big Data in enterprise IT environments.
Collaborate with project managers, resource managers, IT teams, data scientists, and analysts to gather requirements, define project scope, and deliver reliable, model-ready datasets.
Design, build, and maintain ETL pipelines for ingesting and transforming data into a cloud-based R&D data lake.
Develop reusable data models and libraries to streamline common analytics and ETL use cases.
Implement data quality through validation, monitoring, and anomaly detection mechanisms.
Embed security and compliance through RBAC, data lineage, auditing, and regulatory standards.
Optimize ETL pipelines for performance, scalability, and cost efficiency.
Automate deployments and operations using CI/CD, Infrastructure as Code, and ETL jobs.
Monitor and troubleshoot production pipelines, resolve data and platform issues, and continuously improve reliability.
Master’s degree or equivalent practical experience in Data Engineering, Software Engineering, Computer Science, or a related technical field.
Hands-on experience with AWS data lake services, including AWS Glue, S3, Athena, and Lake Formation, covering cataloging, governance, ETL orchestration, and secure data access.
Extensive experience designing and implementing ETL pipelines in Databricks, including migration of cloud-based data lakes and ETL workflows to Databricks.
Strong experience with Delta Lake, including Delta table design, performance optimization, schema evolution, and versioned data management.
Strong experience with cloud-native engineering across AWS/Azure, with a primary focus on AWS data lake environments.
Hands-on experience with Infrastructure as Code, CI/CD, DevOps/MLOps practices, AWS CDK, Ansible, and GitLab CI.
Advanced proficiency in Python and SQL, with the ability to develop robust, maintainable, and reusable code frameworks.
Strong knowledge of observability, data lineage, data quality frameworks, metadata management, and secure data access patterns.
Expertise in cluster and job tuning, job orchestration, storage optimization, and cost management in large-scale data lake environments.
Familiarity with Agile and Scrum methodologies, including sprint planning, backlog refinement, iterative delivery, and cross-functional collaboration.
Strong communication, stakeholder management, problem-solving, and collaboration skills.
Benefits
Fixed Term Employment Contract
Work-Life Balance
Flexible Work Mode
What GeekSoft Consulting Offers
International, collaborative consulting culture with clear career development paths.
Comprehensive Dutch benefits package emphasizing well-being, mobility, and career growth.
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