Data warehouses (dwh) and data lakes administration
Data pipeline architecture design and implementation
Etl processes and best practices
Administer and enhance the enterprise data platform, including Data Warehouses (DWH) and Data Lakes, ensuring optimal performance and scalability
Job Summary
Administer and enhance the enterprise data platform, including Data Warehouses (DWH) and Data Lakes, ensuring optimal performance and scalability.
Design, implement, and maintain robust and reliable data pipeline architecture to meet business needs, utilizing SQL and big data technologies such as Hadoop, Spark, and Kafka.
Partner with stakeholders, including product teams, data experts, and architects, to resolve technical issues and support data infrastructure needs.
Matching Summary
Administer and enhance the enterprise data platform, including Data Warehouses (DWH) and Data Lakes, ensuring optimal performance and scalability.
Skills & Requirements
Must-have
Data Warehouses (DWH) and Data Lakes administration
Data pipeline architecture design and implementation
ETL processes and best practices
DevOps and CICD for data systems
Terraform experience
Big data tools (Hadoop, Spark, Kafka)
SQL and NoSQL databases
Nice-to-have
Automated data pipeline tools
Microsoft cloud services (Azure, Databricks)
Stream-processing systems
Kubernetes for container orchestration
Power BI for data visualization
Agile mindset and collaboration
Key Requirements
Bachelor's degree in Computer Science, Engineering, or related field
6+ years industry experience with data, coding, and scripting
Solid knowledge of CS fundamentals
Strong experience with Terraform
Experience with big data tools: Hadoop, Spark, Kafka
Experience with relational SQL and NoSQL databases