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Senior DataOps Engineer

Everops
CompanyEverops
CategoryEngineering
LocationSan Francisco
RemoteRemote
EmploymentNot stated
LevelSenior
SalaryNot stated by the employer
Posted6 Jul 2026
Last verified30 Jul 2026
SourceEmployer career page (ashby)
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Description
WHAT IS EVEROPS? Some of the world’s most advanced and innovative global enterprise software and tech companies have trouble finding engineering partners that have the ability to perform highly complex deliveries and services that match their rigorous standards. These teams need a partner that can co-own problems from within their own development environment. Enter EverOps – the premier Embedded Service Provider. We partner directly with our customer engineering and operations teams to help them assess and address a variety of delivery and service related issues in the DevOps and DataOps space. THE CHALLENGE EverOps is looking for a Senior DataOps Engineer who combines deep database administration expertise with cloud data platform and pipeline engineering skills. This role sits on a platform team and requires someone who can own the full data operations stack, from SQL Managed Instance performance troubleshooting and Azure Data Factory pipeline monitoring to Azure infrastructure diagnostics, with minimal direction. You will be a critical operational resource and must be comfortable making independent decisions, including during off-hours coverage. AUTOMATION-FIRST MINDSET A core expectation of this role is a relentless focus on identifying manual processes within the data stack and replacing them with reliable, repeatable automation. Whether it’s a DBA task that requires someone to log in and click buttons, a pipeline restart that gets triggered by a Teams message, or a database refresh that runs off a shared checklist. This engineer sees those as backlogs, not workflows. You will be expected to actively inventory manual toil, prioritize it, and ship automation that eliminates it. This is not a secondary responsibility, it is a core deliverable of the role. THE MISSION As a Senior DataOps Engineer at EverOps you will join our U.S.-Based Virtual Operating Center (your home office), working with a team of dynamic engineers embedded on a platform team managing a production Azure data environments. You will not be siloed, the work spans the full data and application platform stack. Our existing team is eager to empower and mentor each new hire to ensure success. ON-CALL & OFF-HOURS EXPECTATIONS This role participates in a rotating on-call schedule that includes off-hours coverage. Operational incidents, pipeline failures, and database issues do not follow business hours, and this team provides extended coverage to ensure continuity for our customers. You will be expected to: - Participate in a scheduled off-hours on-call rotation shared across the team - Respond to and resolve incidents, failed pipeline runs, and database alerts outside of standard business hours when on-call - Perform planned off-hours maintenance tasks such as database refreshes, certificate renewals, and deployment slot swaps that require low-traffic maintenance windows - Produce clear written shift handoff notes and daily operational reports so the next engineer on rotation has full situational awareness WHAT YOU’LL DO - Own day-to-day operations of Azure SQL Managed Instance environments including performance monitoring, troubleshooting blocking and long-running queries, index and statistics maintenance, and SQL Agent job management - Monitor, triage, and restart Azure Data Factory pipeline runs; understand ETL dependencies and troubleshoot integration failures between ADF, SQL MI, and Azure Storage - Manage SSIS package execution and re-runs, including HR/personnel integration processes and common failure pattern diagnosis - Support Azure infrastructure operations including App Services, App Service Environments, deployment slots, WebJobs, Storage Accounts, and certificate lifecycle management - Validate and test database backups, restores, and job chains to ensure recoverability - Continuously inventory manual operational tasks across the data stack and prioritize them for automation - Design and implement autom
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