We are growing the maintenance engineering team: the people who take on the hardest client cases and keep the platform healthy. This is not a call centre and not a first line: what reaches this role are the cases that require reading code, writing SQL and proving the root cause with facts. The role has no direct client communication: all communication is internal, with English-speaking colleagues.
In this role you will:
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Investigate escalated client tickets, from the symptom in the UI down to the root cause in the code, the database or data.
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Write SQL against production PostgreSQL replicas to reconcile platform data, API and MMP trackers.
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Read the product’s Python / Django code and run targeted operations via management commands and the Django shell.
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Diagnose data pipelines (Airflow) and services running in Kubernetes; work with logs and metrics in Grafana / VictoriaLogs.
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Grow the platform’s monitoring: build dashboards and alerts for whatever breaks most often, so that problems are found before clients report them.
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Deliver conclusions to the product and engineering teams: a proven root cause, a reproducible bug report, a clear investigation summary.
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Turn one-off investigations into runbooks and automations: we are actively building an internal AI toolkit (skills for Claude Code) and expect you to develop it further.
About you:
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2+ years of experience in L2 technical support or a similar technical troubleshooting role (QA, SRE / DevOps, backend).
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Confident SQL: joins, aggregations, window functions, comfortable working with large production datasets, without putting production at risk.
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Experience in troubleshooting applications, APIs and databases using various tools and approaches.
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Experience in analyzing application and server logs: ability to parse and read log files.
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Linux and Bash scripting basics, confident work in the command line.
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Experience with monitoring systems (Grafana, Prometheus / VictoriaMetrics, Datadog, etc.): not only reading ready-made dashboards, but building monitoring for the task at hand: metrics, dashboards, alerting.
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Experience with REST APIs: reading the documentation, sending requests, interpreting responses and errors.
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Experience with utilizing AI-based tools for work-related tasks: log and data analysis, drafting documentation, automating routine work.
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Confident use of Google Sheets / Microsoft Excel.
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A systematic approach to investigations: hypothesis → check → proof, rather than “restarted it and it works now”.
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Focus on the outcome for the client: the ability to prioritise and run several investigations in parallel.
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Good written English (B2 and above): internal communication with English-speaking colleagues, tickets and documentation are in English.
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Care when working with production data: understanding the difference between read-only and “let me just fix it in the database”.
It would be nice if you have:
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Python at the level of “I read other people’s code and write scripts for myself”; familiarity with Django is a strong plus.
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Experience with Apple Ads, mobile performance marketing or MMPs (AppsFlyer, Adjust, Singular).
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Kubernetes (kubectl) and Airflow at a user level.
https://gsz.gov.by/registration/employer/vacancy/2019497/detail-public/