Coderoad Operations Engineer – Data Operations at CodeRoad investigates and resolves data issues and monitors data pipelines. Supports data reporting, maintains data integrity, and automates operational workflows.
Responsibilities
Investigate & Resolve Data Issues: Identify, investigate, and troubleshoot missing, duplicate, inconsistent, or unexpected data in operational systems. Use SQL queries to trace issues, identify root causes, and help implement appropriate resolutions.
Monitor Data Pipelines & Scheduled Jobs: Monitor data processing workflows, scheduled jobs, and pipeline executions. Investigate failures, identify bottlenecks, and coordinate troubleshooting to help maintain reliable data flows.
Support Data Reporting & Refresh Processes: Troubleshoot data discrepancies, failed refreshes, and issues affecting reporting tools and dashboards, working with the appropriate teams to restore accurate and reliable data.
Maintain Data Integrity: Perform approved data corrections and operational changes while following established procedures, documentation, and data integrity standards.
Automate & Improve Operational Workflows: Identify opportunities to streamline recurring investigations, reduce manual effort, and improve operational efficiency through scripting, automation, and AI-assisted tools. Proactively experiment with AI solutions to accelerate troubleshooting and find smarter ways to solve everyday problems.
Collaborate Within the Infrastructure Team: Work as part of a three-person infrastructure team to investigate and resolve data-related operational issues. Track incidents and resolutions through ticketing systems and collaborate with developers, IT Operations, and business stakeholders as needed.
Relevant Experience: 1–3 years of professional experience in IT Operations, Data Operations, application support, database support, or a similar technical troubleshooting role.
SQL & Database Fundamentals: Hands-on experience writing SQL queries to investigate data issues, validate records, identify discrepancies, and troubleshoot problems. Familiarity with relational databases, particularly Microsoft SQL Server, is preferred.
Data Processing & Pipeline Knowledge: Basic understanding of data pipelines, ETL/ELT processes, scheduled jobs, and how data moves between operational systems and reporting environments. Exposure to tools such as Azure Data Factory, Airflow, or SQL Server Agent is a plus.
Reporting & Troubleshooting: Familiarity with data reporting tools, dashboards, or data refresh processes. Experience with Tableau or similar BI platforms is an advantage.
Scripting & Automation: Basic experience with Python, PowerShell, or other scripting tools is a plus. A proactive approach to leveraging AI-assisted coding and automation tools to simplify workflows, reduce repetitive work, and solve operational problems is especially desirable.
AI-Driven Problem Solving: A proactive mindset toward adopting AI tools to investigate issues, automate repetitive tasks, improve troubleshooting, and identify opportunities to make daily operations more efficient. Curiosity, initiative, and a willingness to experiment with emerging AI technologies are highly valued.
