Job Description
ProArch is hiring a skilled Azure Data Engineer to join our team. As an Azure Data Engineer, you will be responsible for designing, implementing, and maintaining data processing systems using Azure technologies. Additionally, you will collaborate with cross-functional teams to understand business requirements, identify opportunities for data-driven improvements, and deliver high-quality solutions. If you have a strong background in Azure data tools and technologies, excellent problem-solving skills, and a passion for data engineering, we want to hear from you!
Responsibilities:
- Design, develop, and implement data engineering solutions on the Azure platform
- Create and maintain data pipelines and ETL processes
- Optimize data storage and retrieval for performance and scalability
- Collaborate with data scientists and analysts to build data models and enable data-driven insights
- Ensure data quality and integrity through data validation and cleansing
- Monitor and troubleshoot data pipelines and resolve any issues
- Stay up-to-date with the latest Azure data engineering best practices and technologies
Requirements
- Excellent communication skills
- Strong experience in Python/Pyspark
- The ability to understand businesses concepts and work with customers to process data accurately.
- A solid of understanding Azure Data Lake, Spark for Synapse (or Azure Databricks), Synapse Pipelines (or Azure Data Factory), Mapping Data Flows, SQL Server, Synapse Serverless/Pools (or SQL Data Warehouse).
- Experience with source control, version control and moving data artifacts from Dev to Test to Prod.
- A proactive self-starter, who likes deliver value, solves challenges and make progress.
- Comfortable working in a team or as an individual contributor
- Good data modelling skills (e.g., relationships, entities, facts, and dimensions)
Qualification
Bachelor's Degree
Key skill Required
- SQL
- Python
- SQL Server
- Azure
- Data Engineering
- Data Lake
- Data Processing
- Azure Data Factory
- Communication
- Data Pipelines
- Data Quality
- Data Storage
- Data Validation
- Data Warehouse
- Design
- Engineering Solutions
- Proactive
- Pyspark
- Scalability
- SPARK
- Validation
- Version Control
