Lead Data Engineer With Snowflake

NoSQL-to-RDBMS Mapping: Flatten and normalize complex, nested JSON data from MongoDB into structured relational tables. Pipeline Development: Build and manage reliable ETL pipelines to ingest data from MongoDB, process it via Snowflake, and load it into MySQL. Database Optimization: Design, index, and tune target MySQL databases to ensure high performance and strict data integrity. Snowflake Utilization: Leverage Snowflake's variant handling capabilities to efficiently stage, parse, and transform semi-structured data.

Responsibilities

Understanding the business requirements; Writing code and implementing the proposed solutions; Creating data pipelines, versioning and change management; Manage the complexity inherent in versioned data pipelines; Develop ETL/ELT processes to help extract and manipulate data from multiple sources; Design, build and maintain batch or real-time data pipelines in production; Automate data workflows such as data ingestion, aggregation, and ETL processing; Logging and instrumentation of pipelines and services; Ensure data accuracy, integrity, privacy, security, and compliance through quality control procedures; Train and mentor junior engineers; Flatten and normalize complex, nested JSON data from MongoDB into structured relational tables; Build and manage reliable ETL pipelines to ingest data from MongoDB, process it via Snowflake, and load it into MySQL; Design, index, and tune target MySQL databases to ensure high performance and strict data integrity; Leverage Snowflake's variant handling capabilities to efficiently stage, parse, and transform semi-structured data

Requirements

Proficiency in MongoDB; proficiency in MySQL; proficiency in Snowflake SQL

Nice to have

Python (including ETL frameworks like Rivery or Informatica)

Benefits

Flexibility & Well-being (remote-first approach); Global Community; Your Voice Matters; Growth & Development; fitness offerings; mental health plans (country-dependent); generous time off