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 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
AWS Data Analytics Technology Stack
Python and PySpark
Snowflake data warehousing
AWS Cloud development
Data ingestion to Snowflake
DBT for ELT pipeline development
Advanced SQL and PL/SQL
Nice-to-have
Data governance or lineage tools
Orchestration tools like Airflow
Ab Initio ETL tool knowledge
Stakeholder engagement and requirement elicitation
Understanding infrastructure setup
Data Marts and Data Warehousing concepts
Key Requirements
At least two major project implementations
Leadership responsibilities or individual contributor technical expertise