Snowflake Data Engineer

Posted Yesterday
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Hiring Remotely in India
Remote
Senior level
Artificial Intelligence • HR Tech • Professional Services • Software
The Role
Design and maintain scalable Snowflake data warehouses and ETL/ELT pipelines. Lead Oracle-to-Snowflake migrations, including assessment, mapping, transformation, validation, and reconciliation. Develop data models and advanced SQL workflows, optimize Snowflake performance, troubleshoot pipeline and data quality issues, and support secure, governed, monitored cloud data platforms. Collaborate with architects, analysts, application teams, and business stakeholders on enterprise data modernization.
Summary Generated by Built In

This role is for one of Weekday’s clients

Min Experience: 5+ years
Location: Remote (India), India
JobType: full-time

We are seeking an experienced Snowflake Data Engineer with 5–8 years of hands-on experience in data engineering, data warehousing, and large-scale data migration. The ideal candidate will have strong expertise in Snowflake Data Warehousing, ETL/ELT development, and Oracle-to-Snowflake migration. You will be responsible for designing scalable data solutions, developing efficient data pipelines, and supporting the modernization of enterprise data platforms.


RequirementsKey Responsibilities
  • Design, develop, and maintain scalable data warehouse solutions using Snowflake.
  • Develop robust and optimized ETL/ELT pipelines for ingesting, transforming, and loading data from multiple source systems.
  • Lead and execute Oracle-to-Snowflake migration activities, including data assessment, mapping, transformation, validation, and reconciliation.
  • Analyze existing Oracle databases, stored procedures, ETL workflows, and data models to determine appropriate migration strategies.
  • Design and implement efficient data models, schemas, tables, views, and data structures in Snowflake.
  • Develop SQL queries, transformations, and data processing workflows while ensuring performance and maintainability.
  • Optimize Snowflake workloads through appropriate warehouse sizing, query optimization, clustering, partitioning, and resource management.
  • Build data pipelines that ensure data quality, reliability, accuracy, and timely availability for downstream analytics and reporting.
  • Perform data validation and reconciliation between Oracle and Snowflake during migration and post-migration activities.
  • Collaborate with data architects, analysts, application teams, and business stakeholders to understand data requirements.
  • Troubleshoot data pipeline failures, performance issues, and data quality problems.
  • Establish and follow best practices for data security, governance, documentation, and operational monitoring.
  • Contribute to the modernization of legacy data platforms and migration from traditional data warehouses to cloud-based solutions.
Must-Have Skills
  • 5–8 years of experience in Data Engineering or Data Warehousing.
  • Strong hands-on experience with Snowflake Data Warehousing.
  • Strong expertise in ETL/ELT development and data pipeline engineering.
  • Proven experience with Oracle-to-Snowflake migration projects.
  • Advanced SQL skills with experience working with complex queries, joins, transformations, and performance optimization.
  • Strong understanding of data warehousing concepts, dimensional modeling, fact and dimension tables, and data integration patterns.
  • Experience with data migration, reconciliation, validation, and troubleshooting.
  • Good understanding of cloud-based data platforms and modern data engineering practices.
Good-to-Have Skills
  • Experience with ETL tools such as Informatica, Talend, Matillion, or similar platforms.
  • Exposure to Python for data engineering and automation.
  • Experience with AWS, Azure, or GCP data services.
  • Knowledge of Snowflake features such as Streams, Tasks, Snowpipe, Dynamic Tables, and Time Travel.
  • Familiarity with CI/CD, Git, and DevOps practices.
  • Experience working in Agile development environments.
Qualifications

Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field is preferred.

The ideal candidate should be analytical, detail-oriented, and capable of working independently while collaborating effectively with cross-functional teams. Strong communication and problem-solving skills are essential for successfully managing complex data migration and engineering initiatives.

Skills Required

  • 5-8 years of experience in data engineering or data warehousing
  • Strong hands-on experience with Snowflake data warehousing
  • Strong expertise in ETL/ELT development and data pipeline engineering
  • Proven experience with Oracle-to-Snowflake migration projects
  • Advanced SQL skills, including complex queries, joins, transformations, and performance optimization
  • Understanding of data warehousing, dimensional modeling, fact and dimension tables, and data integration patterns
  • Experience with data migration, reconciliation, validation, and troubleshooting
  • Understanding of cloud-based data platforms and modern data engineering practices
  • Experience with Informatica, Talend, Matillion, or similar ETL tools
  • Exposure to Python for data engineering and automation
  • Experience with AWS, Azure, or GCP data services
  • Knowledge of Snowflake Streams, Tasks, Snowpipe, Dynamic Tables, and Time Travel
  • Familiarity with CI/CD, Git, and DevOps practices
  • Experience working in Agile development environments
  • Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field
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The Company
Year Founded: 2021

What We Do

Weekday is an AI-powered recruitment platform that helps startups hire top-tier engineering and product talent. By leveraging a massive database of white-collar professionals and advanced outreach tools, the company streamlines the hiring process through automated sourcing, AI-driven resume screening, and white-glove contingency services. Their mission is to modernize recruitment by enabling companies to discover and engage passive candidates efficiently, ensuring high-quality hires for critical roles.

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