Tasks:
- * Build and maintain data ingestion and integration pipelines
- * Build and maintain data lakes and data warehouses
- * Collaborate with business, analytics, BI, and data science teams
- * Define data architecture standards and best practices
- * Design and evolve scalable, secure data architectures
- * Develop ETL/ELT pipelines
- * Ensure data quality, lineage, security, and governance
- * Implement and evolve cloud data platforms
- * Integrate data from enterprise systems and applications
- * Optimize data storage, transformation, and consumption
- * Process and transform large data volumes
- * Provide technical guidance to multidisciplinary teams
Perks/Benefits:
Skills/Tech stack required:
[Agile methodologies] [Big Data] [Big data processing] [Cloud Data] [Cloud Data Platforms] [Cognite] [Data Architecture] [Databricks] [Data Engineering] [Data Governance] [Dataiku] [Data Lakes] [Data Lineage] [Data Modeling] [DataOps] [Data platforms] [Data Processing] [Data Quality] [Data Security] [Data Warehouses] [ELT] [ETL] [Git] [Python] [SAP Datasphere] [SQL] [Systems Integration]
Educational requirements:
[Bachelor's Degree]
Role(s):
[Data Engineer] [Engineer]