Production Data Reliability Engineer

Socket.dev; Norcross (GA); On-site; USD 90,000 - 120,000; Full time

Benefits offered by this job

Medical, dental, and vision coverage

401(k) with company match

Generous PTO

Paid parental leave

Volunteer time off

Job summary

Credigy is seeking a Production Support Engineer to join our Data and Automation team in Norcross, GA. You will monitor, troubleshoot, and improve production data pipelines across cloud and legacy systems, owning routine issues with limited supervision.

The ideal candidate has strong SQL and ETL fundamentals, hands-on Snowflake experience, and can collaborate across Data Engineering, Analytics, and business users to resolve production challenges.

Qualifications

• 3+ years in data engineering, BI development, ETL, data operations, or related technical role.
• Strong SQL knowledge, MS SQL Server, and T-SQL troubleshooting abilities.
• Hands-on ETL/data integration experience with SSIS, ADF, Informatica or similar tools.
• 2+ years with Snowflake in production environments.
• Understanding of data pipelines, ETL/ELT, data validation, and data modeling.

Responsibilities

• Monitor and support production data pipelines, jobs, integrations, and loads across SQL Server, Snowflake, SSIS, ADF, and other tools.
• Own routine production tickets (Jira) from investigation to resolution; escalate complex issues as needed.
• Maintain data quality checks, monitoring, and durable fixes for reliability.

Skills

SQL

MS SQL Server

T-SQL

ETL

Snowflake

Data pipelines

Troubleshooting

Jira Service Mgmt

Education

Bachelor's degree

Tools

SSIS

Azure Data Factory

Informatica

dbt

GitHub

CI/CD

Job description

Credigy is seeking a Production Support Engineer to join our Data and Automation team in Norcross, GA. You will monitor, troubleshoot, and improve production data pipelines across cloud and legacy systems, owning routine issues with limited supervision.

The ideal candidate has strong SQL and ETL fundamentals, hands-on Snowflake experience, and can collaborate across Data Engineering, Analytics, and business users to resolve production challenges.