The Data & AI Operations Team is growing rapidly at Empired. We are looking for dedicated person to be a key member of this team to support some of our flagship clients.
As a Data Engineer in the Operations Team, you are a primary point of contact providing tier one support to clients. You are responsible for providing operational/functional support, resolution of level two incidents and requests, monitoring and ensuring service level agreement (SLA) compliance and providing Azure Data expertise to ensure that we achieve our goal of being easy to do business with.”
Please apply if you're experienced in the below:
3+ years experience in ETL Developer, Data Operations, or similar role
Very strong SQL skills with deep experience in ETL/ELT and data modelling
Develop complex ETL using SSIS, Azure Data Factory or Azure Databricks
Hands-on experience with Spark, Event Hub and/or Stream Processing is highly desirable
Strong knowledge of the Microsoft cloud data platform including Power BI, Azure Data Factory, Data Lake, SQL DB, Azure Synapse, and Databricks.
Knowledge of Data Catalogue will be advantageous
Background knowledge or hands-on experience of the Microsoft DevOps stack including CI/CD toolsets and processes
A proven track record in supporting data-oriented solutions utilising big data, data warehousing, operational insight, data management or business intelligence.
Strong technical disposition for monitoring, observability, and performance management
Instincts for identifying, documenting and mitigating risks
Experience troubleshooting and performance tuning
Attention to detail and a fervent belief in a Duty of Care to our clients
Strong knowledge share and commitment to professional documentation
Be familiar with the data challenges faced by organisations within any of the following sectors: Mining, Government, Higher Education, Health & Social Care, Engineering, Manufacturing.
Clear written and verbal communications; able to communicate with a wide range of people and to gather requirements.
You may have experience in ArcGIS (but this is not mandatory)