Overview

Location: Offshore - India / 100% Remote

Duration: 6 months initially, with a strong possibility of extension based on performance

Work Time: 2:00 to 11:00 pm IST

Interview process: 2 levels of Live SQL Tests (60 - 75 minutes each) and 1 Technical Interview.

Hiring Manager's Notes:

• Core Skill: Heavy emphasis on strong SQL development (complex SQL queries and stored procedures).
• Data Platform: Snowflake is highly preferred, but not mandatory.

Key Responsibilities

• Building scalable data pipeline architectures (ELT/ETL), batch/near-real-time processing, and optimizing data infrastructure.
• Tools & Integrations: Apache Airflow, Azure Data Factory, Informatica, Matillion, dbt, or equivalent.
• Source systems: Experience integrating data from SAP, Salesforce, Shopify, or similar enterprise applications.

Position Summary

We are seeking enterprise-grade Senior Snowflake Data Engineers with a decade of proven data engineering mastery to lead the architecture, optimization, and scaling of our data infrastructure. In this role, you will design robust ELT/ETL pipelines, build scalable data warehouse models, and translate data strategies into high-performance products. You will leverage advanced Snowflake features, modern programming environments, and secure cloud platforms to provide clean, reliable data assets to cross-functional teams including Consumer Insights, Supply Chain, and Finance.

Required Skills

• 10+ years of dedicated Data Engineering experience, with at least 5+ years of core specialization in Snowflake.
• Deep practical expertise in Snowflake security and administration (RBAC management, virtual warehouses) and advanced features (Streams, Tasks, Zero-Copy Clone, Time Travel, and custom File Formats).
• Expert-level SQL development background with advanced mastery of structural query writing, indexing, and performant Stored Procedures.
• High proficiency working with no-code/low-code ETL orchestration tools alongside strong programmatic capabilities in at least one modern language (Python, Java, or C).
• Strong hands-on experience deploying data frameworks within major public cloud computing ecosystems (AWS, Azure, or GCP).
• Deep understanding of data warehousing paradigms, data modeling (Star/Snowflake schema), cleansing methodologies, and rigid data governance guardrails.