Production Support Engineer

Credigy•Norcross, GA

4h•Hybrid

About The Position

Credigy is seeking a Production Support Engineer to join our Data and Automation team. This role is responsible for supporting, monitoring, troubleshooting, and improving production data pipelines across both modern cloud platforms and legacy systems. You will help ensure critical data processes run reliably, investigate production issues, and contribute to small enhancements and automation that improve the stability and maintainability of the data environment. This is a hands-on, mid-level role for an engineer who can independently own routine production issues while continuing to grow across a broad data platform. The ideal candidate has strong SQL and ETL fundamentals, hands-on Snowflake experience, and the ability to troubleshoot production data processes with limited supervision. Complex architectural or high-severity issues would be escalated to senior engineers as appropriate. Please note that we are unable to provide visa sponsorship for this role. Candidates must be legally authorized to work in the United States now and in the future without employer sponsorship.

Requirements

3+ years of experience in data engineering, BI development, ETL development, data operations, application support, or a related technical role.
Strong working knowledge of SQL, preferably MS SQL Server and T-SQL, with the ability to independently troubleshoot queries, stored procedures, data quality issues, and production failures.
Hands-on experience supporting or developing with ETL/data integration technologies such as SSIS, Azure Data Factory (ADF), Informatica, or similar tools.
2+ years of hands-on experience with Snowflake in a production environment.
Strong understanding of data pipelines, ETL/ELT concepts, data validation, and core data modeling principles.
Demonstrated experience independently troubleshooting and resolving technical or data issues in a production or business-critical environment.
Bachelor’s degree in Computer Science, Information Systems, Statistics, or a related field (or equivalent practical experience).

Nice To Haves

Experience supporting and troubleshooting Snowflake data pipelines, queries, and scheduled workloads.
Experience using Python or scripting for data processing, troubleshooting, or automation.
Experience with Informatica, dbt, or other modern data transformation/integration tools.
Experience with GitHub, CI/CD, monitoring, or automated deployment processes.
Familiarity with data quality, data governance, Azure services, or other data platform technologies.

Responsibilities

Monitor and support production data pipelines, scheduled jobs, integrations, and data loads across SQL Server, Snowflake, SSIS, Azure Data Factory (ADF), and other data integration tools.
Own routine production support tickets (Jira Service Management) from investigation through resolution, including troubleshooting, stakeholder communication, remediation, and follow-up. Escalate complex architectural, high-severity, or cross-platform issues as appropriate.
Perform root cause analysis and maintain data quality checks, monitoring, and durable fixes that improve the reliability and accuracy of production data processes.
Maintain and enhance existing ETL processes, address bug fixes and small development requests, and improve the performance and maintainability of production workflows.
Identify repetitive support activities that can be simplified, documented, or automated to reduce recurring operational effort.
Partner with Data Engineering, Analytics, business users, and other internal teams to resolve production issues and communicate status, impact, and resolution clearly.
Create and maintain troubleshooting guides, runbooks, and technical documentation to support consistent and efficient issue resolution.