Provide critical technical execution and analytical leadership, acting as a driving force in translating raw data into robust, production-ready data models.
Ensure cross-functional teams have seamless access to un-compromised, highly performant, and real-time datasets.
Responsible for dismantling legacy data workflows, engineering scalable data pipelines, and establishing rigorous validation standards to guarantee data reliability and pipeline health.

3 to 5+ years of professional experience in dedicated data-focused engineering or advanced analytics roles.
Exceptional ability to write, debug, and tune complex SQL queries for heavy data transformations, validation, and analytics reporting.
Strong hands-on experience using Python to build custom data processing workflows, automation scripts, and pipeline connectors.
Direct experience designing, managing, and indexing performant data models natively within Snowflake.
Production experience developing modular, tested, and documented data transformation code using dbt.
Practical familiarity with AWS cloud environments (e.g., S3, EC2, or related data orchestration services) supporting scalable storage and execution.
Strong understanding of data validation, data quality frameworks, and pipeline health troubleshooting.
Familiarity with next-generation data orchestrators like Dagster or Apache Airflow (Nice to have).
Prior experience working with marketplace dynamics, transactional data, matching algorithms, or user-behavior metrics (Nice to have).

Data Engineer – Analytics, Modeling

Key skills