We are seeking a skilled Azure Data Engineer to design, build, and maintain scalable data solutions in the Microsoft Azure cloud ecosystem. The ideal candidate will have strong experience in data pipelines, cloud-based data integration, and modern data warehousing concepts. This role involves working closely with data analysts, architects, and business stakeholders to deliver high‑quality, reliable data solutions.
Key Responsibilities
- Design, develop, and maintain data pipelines using Azure Data Factory, Databricks, or Synapse.
- Build and optimize data storage solutions such as Azure Data Lake Storage (ADLS), Azure SQL DB, Azure Synapse Analytics.
- Develop and manage ETL/ELT data workflows for batch and real-time data processing.
- Implement data models, star/snowflake schemas, and optimize database performance.
- Ensure data quality, governance, and compliance across data platforms.
- Develop and deploy CI/CD pipelines for data components using Azure DevOps or GitHub.
- Collaborate with data architects and BI teams to translate requirements into technical solutions.
- Work with structured and unstructured data using Python, SQL, and Spark.
- Monitor and troubleshoot data pipelines, ensuring system reliability and high availability.
- Implement security best practices including RBAC, data encryption, and access controls.
Required Skills & Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
- 5–7 years of experience as a Data Engineer (or relevant role).
- Strong expertise in:
- Azure Data Factory
- Azure Databricks / Apache Spark
- Azure SQL, Synapse Analytics, and ADLS
- SQL and Python
- Experience with data modelling and performance tuning.
- Knowledge of CI/CD, Git, and DevOps practices.
- Familiarity with event-based processing (Event Hub, Kafka, Stream Analytics) is a plus.
- Strong understanding of data governance, security, and compliance frameworks.