Senior Analytics Engineer (dbt)

Location: Remote or office-based in Armenia, Bulgaria, Cyprus, Georgia, Kazakhstan, Latvia, Poland, Romania, Serbia, and Ukraine; listed locations include Almaty, Astana, Belgrade, Cluj-Napoca, Dnipro, Kharkiv, Krakow, Kyiv, Larnaca, Lodz, Lublin, Lviv, Odesa, Riga, Sofia, Tbilisi, Varna, Warsaw, Wroclaw, and Yerevan.

Company

hirify.global provides software engineering and technology consulting services.

What you will do

• Build governed dbt models for critical business metrics.
• Develop Lightdash dashboards and metric trees to monitor metric quality, freshness, and drift.
• Create automated alerts for metric owners and document metric definitions, calculations, ownership, and sources.
• Align metric definitions across business teams and collaborate with BI leads, data engineering leads, and business owners.
• Build and maintain Airflow pipelines for ingesting external API data into Redshift, including improvements to the Zendesk pipeline.
• Reconcile ticket volume and CSAT data with source systems and migrate or retire legacy dbt models and Lightdash content using usage data and user communication.

Requirements

• Strong experience in analytics engineering or data engineering, including strong experience with dbt.
• Advanced SQL skills and experience with Amazon Redshift.
• Experience with Lightdash or a similar dbt-native BI tool.
• Experience with Python and Airflow for API-based data ingestion.
• Experience with data quality monitoring, including freshness checks, anomaly detection, and alerting.
• Experience with metric and semantic layer design and data reconciliation against source systems.
• Solid understanding of PII handling and data minimisation.
• Confidence working with non-technical stakeholders.
• Fluent English.

Culture & Benefits

• Work within an established analytics environment and a medium-sized data team of 10–20 people.
• Collaborate cross-functionally with BI and data engineering leads and business owners across the company.
• Focus on clear communication, shared metric definitions, and reliable data delivery.