Senior Data Reliability Engineer
Skills
Azure Data FactoryAzure Data LakeDevopsApplication ServicesData ServicesData As A ServiceDrift
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- 5+ years in Data Engineering Analytics Engineering or data focused SRE DevOps roles
- Strong SQL skills with complex performant queries and transformations
- Hands-on experience with data modelling such as dimensional modelling or star schemas
- Production experience building and maintaining data pipelines with Azure Data Factory or similar orchestration tools
- Hands-on Power BI development including reports DAX measures data models and published dashboards
- Python scripting for data transformation automation and pipeline development
- Experience implementing monitoring and observability for data systems
- Experience working with stakeholders to translate business needs into data solutions
- Understanding of SRE principles including SLIs SLOs error budgets incident response and blameless post mortems
- Familiarity with cloud data platforms with Azure preferred such as Synapse Analytics Azure SQL and Azure Data Lake
Nice to have
- fragmented source consolidation
- DataOps practices
- data quality frameworks
- data governance
- Infrastructure as Code
- Docker and Kubernetes
- modern transformation tools
- AI tooling productivity
Day to day
- Own the reliability quality and scalability of the internal data ecosystem on Azure
- Design data models build ETL and ELT pipelines create dashboards and enable self service analytics with production grade reliability
- Define observability incident response automation and SLOs so data services are trustworthy timely and accessible
Hiring process
- Apply directly through the Careers page on the corporate website