Remote Data Engineer: SQL, Python & Data Warehousing

Gear Partners; Charlotte (NC); Remote; USD 90,000 - 130,000; Full time

Job summary

Gear Partners is seeking a Data Engineer to serve as the lead Technical Analyst for client implementations, gathering data-mapping requirements and overseeing data migration from legacy systems to new databases.

You will work in a remote-first environment based in North Carolina, collaborating with clients to design scalable data solutions, write complex SQL/T-SQL, build Python data pipelines, and ensure data quality across migration projects.

Qualifications

• 3+ years proven experience writing complex SQL queries.
• 2+ years proven experience with Python (data pipelines).
• 2+ years of extensive hands-on experience with designing, developing, and ongoing support of data warehouse environments.
• Strong communication and ability to deliver business value with technical excellence.
• Experience with ATS/CRM software is a plus.

Responsibilities

• Lead stand-up with team to review product specifications and progress.
• Migrations from client legacy databases to new system databases.
• Write T-SQL scripts and perform data deduplication.
• Assist data warehouse team with schema changes for scalability and performance.
• Troubleshoot data inaccuracies and propose remediation plans.
• Review Data Migration Requirements with clients and Business Analysts.
• Conduct data analysis and promote a data-driven culture across the enterprise.

Skills

SQL (complex queries)

Python data pipelines

Data warehouse design & support

Communication & stakeholder engagement

Relational databases

Job description

Gear Partners is seeking a Data Engineer to serve as the lead Technical Analyst for client implementations, gathering data-mapping requirements and overseeing data migration from legacy systems to new databases.

You will work in a remote-first environment based in North Carolina, collaborating with clients to design scalable data solutions, write complex SQL/T-SQL, build Python data pipelines, and ensure data quality across migration projects.