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Senior Data Engineer - L2 - Snowflake Developer

Summary

Design and develop scalable Snowflake-based data architectures, optimize platform performance, and lead Hadoop-to-Snowflake migrations using Snowflake, Snowpark, Python, and PySpark.

About Us:

Kadel Labs is a leading IT services company delivering top-quality technology solutions since 2017, focused on enhancing business operations and productivity through tailored, scalable, and future-ready solutions. With deep domain expertise and a commitment to innovation, we help businesses stay ahead of technological trends. As a CMMI Level 3 and ISO 27001:2022 certified company, we ensure best-in-class process maturity and information security, enabling organizations to achieve their digital transformation goals with confidence and efficiency.

Senior Data Engineer – Snowflake Developer / Architect

Location: Chennai
Work Mode: Work from Office – 5 Days
Shift: Normal / Day Shift

Job Description

We are looking for a Senior Data Engineer / Snowflake Architect with strong expertise in Snowflake, Snowpark, Python, and PySpark to design, develop, and oversee scalable, cloud-native data architectures.

The role will focus on defining target data warehouse architectures, optimizing Snowflake platform performance, and leading the modernization of legacy Big Data environments, particularly migrations from Hadoop to Snowflake.

Key Responsibilities

Snowflake Architecture & Design

  • Design and implement scalable, cloud-native data architectures using Snowflake.
  • Define target-state data warehouse and data platform architectures aligned with business and technical requirements.
  • Establish architecture standards, best practices, and scalable design patterns.
  • Ensure data platforms are designed for performance, reliability, scalability, and maintainability.

Snowflake Development

  • Develop and optimize data solutions using Snowflake, Snowpark, Python, and PySpark.
  • Build scalable data processing and transformation workflows.
  • Implement efficient data models and data pipelines within the Snowflake ecosystem.
  • Ensure high-quality and reliable data processing across enterprise data platforms.

Performance Optimization

  • Analyze and optimize Snowflake workloads and platform performance.
  • Identify performance bottlenecks and implement appropriate optimization strategies.
  • Optimize data processing, queries, and warehouse utilization to improve efficiency and scalability.

Legacy Data Migration

  • Lead and support the migration of legacy Big Data platforms, particularly Hadoop environments, to modern Snowflake-based architectures.
  • Assess existing data platforms and define appropriate migration strategies.
  • Design scalable migration approaches while ensuring data integrity and continuity.
  • Support modernization initiatives to transition legacy workloads to cloud-native data platforms.


Requirements

Required Skills & Expertise

  • Strong hands-on experience with Snowflake.
  • Strong understanding of Snowflake architecture and data warehousing concepts.
  • Experience with Snowpark.
  • Strong programming experience in Python.
  • Hands-on experience with PySpark.
  • Experience designing scalable and cloud-native data architectures.
  • Strong understanding of data warehouse architecture and design.
  • Experience with Hadoop and Big Data environments.
  • Proven experience in Hadoop-to-Snowflake migration or data platform modernization.
  • Strong analytical and problem-solving skills.

Preferred Experience

  • Experience working on large-scale enterprise data platforms.
  • Experience defining target-state architecture and migration roadmaps.
  • Strong understanding of cloud data engineering and modern data warehouse practices.
  • Ability to work with cross-functional technical teams and provide architectural guidance

What You’ll Do

As a Senior Data Engineer / Snowflake Architect, you will play a key role in modernizing enterprise data platforms by designing scalable Snowflake architectures, optimizing platform performance, and driving the migration of legacy Hadoop workloads to modern cloud-native data ecosystems.





Benefits

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