Senior SQL & ETL Developer — Data Migrations & Integration

Appletech; United States; Remote; USD 90,000 - 150,000; Full time

Job summary

Appletech is seeking a highly skilled SQL Developer with deep expertise in SQL Server, ETL workflows, and data migration. You will design, develop, and optimize enterprise-grade data solutions that integrate across systems and support complex transformation logic.

You will collaborate with cross-functional teams, troubleshoot performance issues, and ensure data quality and reliability in large-scale environments.

Qualifications

• 5+ years of experience with SQL databases and related technologies.
• Proficiency in ETL processes.
• Write complex T-SQL queries, stored procedures, views, and functions.
• Experience with data migration from legacy to modern platforms.
• Hands-on experience with MS Excel.
• Collaborate with analysts and stakeholders to understand data requirements.
• Optimize queries for performance and scalability.
• Perform unit testing and assist QA for data accuracy.
• Familiarity with data integration and data quality.
• Excellent problem-solving and analytical skills.
• Ability to work independently.
• Must be ready to work in US ET timezone (6:30 pm - 3 am IST).

Responsibilities

• Design, develop, and optimize enterprise-grade data solutions across systems.
• Lead ETL workflows and data transformation projects.
• Collaborate with analysts and stakeholders to define data requirements.
• Migrate data from legacy systems to modern platforms.
• Ensure data quality, performance, and scalability across systems.

Skills

SQL Server

ETL processes

T-SQL

Data migration

MS Excel

Data integration

Problem solving

Independent work

US ET timezone

Job description

Appletech is seeking a highly skilled SQL Developer with deep expertise in SQL Server, ETL workflows, and data migration. You will design, develop, and optimize enterprise-grade data solutions that integrate across systems and support complex transformation logic.

You will collaborate with cross-functional teams, troubleshoot performance issues, and ensure data quality and reliability in large-scale environments.