> Markdown version of [/jobs/ext/4722215-senior-snowflake-data-engineer](https://www.wearedevelopers.com/jobs/ext/4722215-senior-snowflake-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Senior, Snowflake Data Engineer

- **Company:** Technosoft Corporation
- **Location:** Parsippany-Troy Hills, NJ, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Airflow, Confluence, JIRA, Information Engineering, Data Systems, Data Warehousing, Python (Programming Language), Metadata, Meta-Data Management, Systems Development Life Cycle, SQL Databases, Azure Data Factory, Snowflake, Analytic Functions, Git, Data Lineage, Data Management, Data Pipelines, Sql Tuning
- **Published:** November 14, 2026
- **Apply:** https://www.careerboard.com/us/en/find-jobs-in-United-States/-8B5AA27DAC59689470/

## About the Role

We are looking for an experienced Senior Snowflake Data Engineer with strong expertise in designing, developing, and optimizing enterprise-scale data solutions., * 8+ years of experience in Data Engineering/Data Management.

 * 5+ years of hands-on experience with Snowflake.
 * Strong proficiency in SQL and Python.
 * Experience in Snowflake Data Warehousing and SQL performance tuning.
 * Knowledge of Azure Data Factory and Azure Data Framework.
 * Hands-on experience with Airflow, Informatica, or Automic.
 * Strong understanding of Metadata Management and Data Lineage.
 * Experience with SQL Analytical Functions.
 * Familiarity with Git, Jira, and Confluence.

## Description

The ideal candidate should have hands-on experience with Snowflake, SQL, Python, data warehousing, and data orchestration tools.

 * Design, develop, and maintain enterprise data solutions using Snowflake.
 * Participate in the complete SDLC, including requirements, development, testing, and deployment.
 * Optimize SQL queries and ensure platform performance, scalability, and reliability.
 * Troubleshoot production issues, perform root cause analysis, and implement preventive solutions.
 * Collaborate with engineering teams to deliver high-quality data solutions.
 * Maintain data quality, metadata, and data lineage.