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.
Lead a team performing complex tasks, using well developed professional knowledge and skills to deliver on work that impacts the whole business function.
Harness cutting-edge technology to revolutionise our digital offerings, ensuring unparalleled customer experiences.
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 development
Snowflake data warehousing
DBT for ELT pipeline development
Advanced SQL and PL SQL programming
AWS data pipeline development
Nice-to-have
Data governance or lineage tools
Orchestration tools like Airflow
Abinitio ETL tool knowledge
Stakeholder engagement and requirement elicitation
Infrastructure setup understanding
Data Marts and Data Warehousing concepts
Key Requirements
Hands on experience in python and pyspark
Hands on Experience in developing, testing and maintaining applications on AWS Cloud
Strong hold on AWS Data Analytics Technology Stack
Design and implement scalable solutions using Snowflake
Experience in Data ingestion to Snowflake
Experience in using DBT with snowflake
Experience in Writing advanced SQL and PL SQL programs
Experience in AWS data pipeline development
Hands On Experience for building reusable components using Snowflake and AWS Tools/Technology
Worked at least on two major project implementations