обновлено 4 дня назад
Data Engineer (Azure Data Factory)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Engineer (Azure Data Factory): Supporting an on-premises data warehouse and developing cloud data warehouse pipelines with an accent on SSIS, T-SQL, Azure Data Factory, and medallion architecture. Focus on troubleshooting production failures, building batch and streaming jobs, optimizing data workflows, and maintaining data integrity and governance.
Location: Atlanta, GA, USA
Company
provides offshore data engineering support for on-premises and cloud data warehouse environments.
What you will do
- Monitor, rerun, and troubleshoot production data pipelines and workflows in SSIS and T-SQL.
- Resolve production bugs, investigate recurring failures, document root causes, and provide daily execution status reports.
- Maintain data accuracy and integrity while implementing temporary workarounds to minimize downtime.
- Gather business requirements and define data models and ETL strategies for cloud data warehouse initiatives.
- Design, develop, test, and optimize batch processing and streaming data pipelines using Azure Data Factory.
- Implement medallion architecture, maintain cloud runbooks, and standardize workflows and operational documentation.
Requirements
- Work location: Atlanta, Georgia, USA.
- Experience supporting on-premises data warehouses with SSIS and T-SQL.
- Experience monitoring and resolving production pipeline and workflow issues.
- Knowledge of cloud data warehouse development, data modeling, and ETL strategies.
- Experience with Azure Data Factory, batch processing, and streaming jobs.
- Understanding of data governance policies, security standards, and operational best practices.
Culture & Benefits
- Collaboration with onshore and offshore data engineering teams.
- Participation in regular stand-ups and technical discussions.
- Focus on best practices, technical debt reduction, knowledge transfer, and documented operations.
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