Remote Data Operations Analyst - ETL & Automation

Fuel Talent; Seattle (WA); Hybrid; USD 65,000 - 90,000; Full time

Job summary

Fuel Talent LLC is seeking a Data Operations Analyst to process inbound client and partner data files into our client's record-keeping systems, operating with day-to-day autonomy under the guidance of the Senior Data Operations Analyst.

The role requires SQL, SSIS exposure, and experience with SQL Server; responsibilities include batch jobs, data quality validation, documentation, and helping migrate manual processes to automated pipelines.

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related technical field; equivalent professional experience may substitute.
• Minimum one year of data operations, file processing, or ETL support experience.
• Experience with SQL Server or another relational database.

Responsibilities

• Processes inbound client and partner files, including eligibility, claims, and contributions, using SQL and SSIS under guidance.
• Operates routine cron-scheduled batch jobs and monitors job completion.
• Maintains legacy VB scripts that support data operations workflows.
• Validates data quality and flags exceptions for senior review.
• Documents data integration patterns and runbooks for assigned domains.
• Coordinates with senior staff on complex data integration issues.
• Contributes to the team's migration of manual file processing to automated pipelines.

Skills

SQL Queries

Data Validation

Documentation

Data Quality Communication

Education

Bachelor's degree in Computer Science, Information Systems, Data Engineering, or related field

Tools

SSIS

VB.NET

Batch Scheduling Systems

Job description

Fuel Talent LLC is seeking a Data Operations Analyst to process inbound client and partner data files into our client's record-keeping systems, operating with day-to-day autonomy under the guidance of the Senior Data Operations Analyst.

The role requires SQL, SSIS exposure, and experience with SQL Server; responsibilities include batch jobs, data quality validation, documentation, and helping migrate manual processes to automated pipelines.