Maestro Data Architect

Design, develop, and maintain ETL/ELT pipelines using Snowflake, SQL, Python, and/or cloud services preferably AWS

Build and optimize data models (staging, warehouse, Datamarts) using best practices such as micro partitioning, clustering, and performance tuning.

Develop and manage data ingestion workflows from structured and semi structured sources (JSON, Parquet, XML, APIs, etc.).

Implementation of business requirements using Snowflake features such as Streams, Tasks, Time Travel, Zero Copy Cloning, and Snowpipe for automated data loads.

Collaborate with Data architects, analysts, and business stakeholders to translate requirements into scalable technical solutions.

Monitor and Troubleshoot pipelines for failures and issues ensuring data quality and integrity.

Document data flows, transformations, and technical processes for maintainability and knowledge sharing

DataArchitect Data Modeling Tool, Database Extract Transform and Load (ETL), Python Programming/Scripting Language, Cloud Computing, SQL (Structured Query Language), Amazon Web Services (AWS), Best Practices, Data Modeling, Data Mart, Performance Tuning/Optimization, Excellent analytical skills and strong understanding of SQL/PLSQL

Job scheduling and orchestration using industry standard tools

Skills/Technology:

Hands-on experience with Cloud based Database, preferably Snowflake

Excellent SQL / PL SQL skills

Basic understanding on AWS

Experience on orchestration / scheduling tool, preferably Tidal

Experience on Python is an advantage

Working experience on Data Warehousing and Modeling

Basic understanding of Banking terminology