Lead Snowflake Data Engineer

VMC Soft Technologies, Inc; Bengaluru Urban; On-site; INR 1,500,000 - 2,700,000; Full time

Job summary

VMC Soft Technologies, Inc is seeking an experienced Snowflake Data Engineer to design, develop, and optimize large-scale data intelligence solutions using Snowflake and related technologies. You will build scalable data pipelines, model data for analytics, and ensure data quality across the warehouse.

The role requires strong Snowflake hands-on expertise, Advanced SQL, and Python or Scala to implement end-to-end data solutions, with exposure to data governance and modern data engineering

Qualifications

• 5+ years of overall IT experience, preferably in Data Engineering / Data Warehousing.
• Strong understanding of Data Warehousing concepts, ETL/ELT processes, and dimensional modeling.
• Strong hands-on experience with Snowflake Data Warehouse.
• Advanced SQL proficiency with complex queries, joins, CTEs, and optimization.
• Experience programming in Python or Scala and building data pipelines.

Responsibilities

• Design, develop, and maintain scalable Snowflake Data Warehouse solutions.
• Develop optimized SQL queries, procedures, and data transformation logic.
• Build and maintain robust ETL/ELT data pipelines for batch and real-time processing.
• Design data models including facts, dimensions, and star/snowflake schemas.
• Implement data ingestion using Snowpipe and other mechanisms.

Skills

Snowflake

Advanced SQL

Python

Data Warehousing

ETL/ELT

Data Modeling

Data Pipelines

Data Orchestration

Data Quality

Semi-Structured Data

Tools

Snowpipe

Kafka

Amazon S3

Snowflake Cortex

Job description

Job Description Snowflake Data Engineer

Experience: 6 12 Years

Locations: Noida, Bangalore, Hyderabad, Bhubaneswar, Kochi, Gurgaon

Primary Skills: Snowflake Data Warehouse, Advanced SQL, Python

Job Overview

We are looking for an experienced Snowflake Data Engineer with 6 12 years of IT experience and strong expertise in Snowflake Data Warehouse, Advanced SQL, Python, data warehousing, ETL, data modeling, and modern data engineering practices. The candidate will be responsible for designing, developing, optimizing, and maintaining large-scale data intelligence solutions using Snowflake and related data engineering technologies.

Required Skills & Experience

• 5+ years of overall IT experience, preferably in Data Engineering / Data Warehousing.
• Strong understanding of Data Warehousing concepts, ETL/ELT processes, and dimensional data modeling.
• Strong hands-on experience with Snowflake Data Warehouse.
• Experience working with Snowflake Functions, SQL, stored procedures, and analytical functions.
• Advanced proficiency in SQL, including complex queries, joins, CTEs, subqueries, window functions, MERGE, and query optimization.
• Strong programming/scripting experience in Python or Scala.
• Experience designing and implementing data pipelines and data orchestration frameworks.
• Hands-on experience with Data Quality, Data Governance, and Analytics solutions.
• Experience implementing large-scale data intelligence solutions using Snowflake.
• Good understanding of Snowflake architecture, performance optimization, micro-partitioning, clustering, caching, and warehouse sizing.
• Experience with semi-structured data, including JSON, XML, and Parquet.
• Good experience with streaming technologies such as Apache Kafka.
• Experience with cloud storage platforms such as Amazon S3 is preferred.
• Strong understanding of data migration and data integration.
• Experience with Slowly Changing Dimensions (SCD) and dimensional modeling.
• Strong understanding of data security, including RBAC, role hierarchy, masking policies, and secure data access.
• Knowledge of Snowflake data sharing and governance.
• Good understanding of architecture and design principles for scalable data platforms.

Key Responsibilities

• Design, develop, and maintain scalable Snowflake Data Warehouse solutions.
• Develop complex and optimized SQL queries, procedures, functions, and data transformation logic.
• Build and maintain robust ETL/ELT data pipelines for batch and near-real-time data processing.
• Design data models including fact tables, dimension tables, star/snowflake schemas, and SCD implementations.
• Develop Python/Scala-based data processing and automation solutions.
• Implement data ingestion pipelines using Snowpipe and other Snowflake ingestion mechanisms.
• Integrate data from cloud storage, databases, APIs, Kafka, and other enterprise data sources.
• Process and transform structured and semi-structured data such as JSON, XML, and Parquet.
• Implement data quality checks, validation, reconciliation, and completeness checks.
• Implement data governance, security, RBAC, masking, and controlled data access.
• Optimize Snowflake workloads through warehouse sizing, query optimization, clustering, caching, and efficient data modeling.
• Design solutions leveraging Snowflake Time Travel, Fail-safe, Streams, Tasks, Dynamic Tables, and other advanced Snowflake capabilities.
• Participate in data warehouse migrations and modernization initiatives.
• Troubleshoot data pipeline, SQL, performance, and data-quality issues.
• Collaborate with architects, analysts, application teams, and business stakeholders to deliver data intelligence solutions.
• Contribute to architecture and design decisions for scalable and high-performance data platforms.
• Where applicable, support Snowflake Cortex and AI/ML workloads for modern data intelligence use cases.

Technical Skills

Mandatory

• Snowflake
• Advanced SQL
• Python / Scala
• Data Warehousing
• ETL/ELT
• Data Modeling
• Data Pipelines
• Data Orchestration
• Data Quality
• Semi-Structured Data

Good To Have

• Apache Kafka
• Amazon S3
• Snowpipe
• Snowflake Streams & Tasks
• Dynamic Tables
• Snowflake Cortex
• Time Travel & Fail-safe
• RBAC & Data Masking
• Data Sharing
• Cloud Data Platforms