31 AuxoAI Jobs

Role Summary :

We are seeking skilled Data Engineers with prior experience on Azure data engineering services and SQL server to join our team. As a Data Engineer, you will be responsible for designing and implementing robust data infrastructure, building scalable data pipelines, and ensuring efficient data integration and storage.

Experience : 6 - 10 years

Notice : Immediate to 30days

Responsibilities :

- Design, develop, and maintain scalable data pipelines and use Azure Data Factory and Azure Stream Analytics

- Collaborate with data scientists and analysts to understand data requirements and implement solutions that support analytics and machine learning initiatives.

- Optimize data storage and retrieval mechanisms to ensure performance, reliability, and cost-effectiveness.

- Implement data governance and security best practices to ensure compliance and data integrity.

- Troubleshoot and debug data pipeline issues, providing timely resolution and proactive monitoring.

- Stay abreast of emerging technologies and industry trends, recommending innovative solutions to enhance data engineering capabilities.

Qualifications :

- Proven experience as a Data Engineer or in a similar role.

- Experience in designing and hands-on development in cloud-based (AWS/Azure) analytics solutions.

- Expert level understanding on Azure Data Factory, Azure Synapse, Azure SQL, Azure Data Lake, Azure App Service, Azure Databricks, Azure IoT, Azure HDInsight + Spark, Azure Stream Analytics

- Knowledge of Dev-Ops processes (including CI/CD) and Infrastructure as code is essential.

- Experience in SQL server and procedures.

- Thorough understanding of Azure Infrastructure offerings.

- Strong experience in common data warehouse modelling principles including Kimball, Inmon.

- Experience in additional Modern Database terminologies.

- Working knowledge of Python or Java or Scala is desirable

- Strong knowledge of data modelling, ETL processes, and database technologies

- Experience with big data processing frameworks (Hadoop, Spark) and data pipeline orchestration tools (Airflow).

- Solid understanding of data governance, data security, and data quality best practices.

- Strong analytical and problem-solving skills, with attention to detail.