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Snowflake Dev strong ETL​/SQL

Job in Lake Mary, Seminole County, Florida, 32746, USA
Listing for: Executive Staff Recruiters / ESR Healthcare
Full Time position
Listed on 2026-10-19
Job specializations:
  • Software Development
    Data Engineering
Salary/Wage Range or Industry Benchmark: 100000 - 130000 USD Yearly USD 100000.00 130000.00 YEAR
Job Description & How to Apply Below

Overview

Snowflake Dev with strong ETL / SQL skills Lake Mary,FL

Experience: 10+ Years

Duration:
Long term Contract

Need Linked In & Passport No with the profile

Responsibilities
  • Design and develop scalable data pipelines and ETL processes using Snowflake.
  • Write optimized, advanced SQL queries for data extraction, transformation, and loading (ETL).
  • Develop, implement, and maintain Snowflake database objects including schemas, tables, views, and stored procedures.
  • Work closely with business analysts, data architects, and data engineers to gather requirements and translate them into technical solutions.
  • Ensure performance tuning, query optimization, and best practices in Snowflake development.
  • Support data migration from legacy platforms to Snowflake.
  • Create and maintain technical documentation related to data pipelines, ETL workflows, and Snowflake models.
  • Perform data quality checks and ensure data integrity across systems.
  • Collaborate with cross-functional teams for project delivery in an agile environment.
Required

Skills and Qualifications
  • 8+ years of experience in SQL development, ETL design, and implementation.
  • 5+ years of hands-on experience working with Snowflake Data Warehouse.
  • Strong knowledge of Snowflake architecture, SnowSQL, and Snowflake security frameworks.
  • Proficient in developing ETL pipelines using tools or custom Python/Spark scripts.
  • Strong understanding of data warehousing concepts and dimensional modeling.
  • Experience with any of the cloud platforms
  • Expertise in performance tuning and query optimization.
  • Knowledge of Git, CI/CD pipelines, and version control for data pipeline deployments
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