Build and maintain systems that collect, store, process, and analyse data, such as data pipelines, data warehouses and data lakes to ensure that all data is accurate, accessible, and secure
Job Summary
Build and maintain systems that collect, store, process, and analyse data, such as data pipelines, data warehouses and data lakes to ensure that all data is accurate, accessible, and secure.
Design and implement scalable and efficient data transformation/storage solutions using Snowflake, and develop processing and analysis algorithms fit for the intended data complexity and volumes.
Collaborate with data scientists to build and deploy machine learning models, and implement Cloud based Enterprise data warehouses with multiple data platforms along with Snowflake and NoSQL environment.
Matching Summary
Build and maintain systems that collect, store, process, and analyse data, such as data pipelines, data warehouses and data lakes to ensure that all data is accurate, accessible, and secure.
Skills & Requirements
Must-have
PySpark
AWS Data Analytics Stack
Snowflake
DBT with Snowflake
Advanced SQL and PL SQL
Data ingestion to Snowflake
Reusable components using Snowflake and AWS
Nice-to-have
Data governance or lineage tools
Orchestration tools like Airflow
Abinitio ETL tool
Cloud based Enterprise data warehouse
NoSQL environment
Stakeholder engagement and requirement elicitation
Key Requirements
At least two major project implementations
Good knowledge of Data Marts and Data Warehousing concepts