Azure Data Engineer

Role & responsibilities

Requirements

4 - 10 years of hands-on experience in designing, developing and implementing data engineering solutions.

Strong SQL development skills, including performance tuning and query optimization.

Good understanding of data concepts.

Proficiency in Python and a solid understanding of programming concepts.

Hands-on experience with PySpark or Spark Scala for building data pipelines.

Ensure data consistency and address ambiguities or inconsistencies across datasets.

Understanding of streaming data pipelines for near real-time analytics.

Experience with Azure services including Data Factory, Functions, Databricks, Synapse Analytics, Event Hub, Stream Analytics and Data Lake Storage.

Familiarity with at least one NoSQL database.

Knowledge of modern data architecture patterns and industry trends in data engineering.

Understanding of data governance concepts for data platforms and analytical solutions.

Experience with Git for managing version control for source code.

Experience with DevOps processes, including experience implementing CI/CD pipelines for data engineering solutions.

Strong analytical and problem-solving skills.

Excellent communication and teamwork skills.

Responsibilities

Azure Certifications related to Data Engineering are highly preferred.

Experience with Azure Kubernetes Service (AKS), Container Apps and API Management.

Strong understanding and experience with BI/visualization tools like Power BI

Preferred candidate profile