
Data Engineer
4 weeks ago
Key Responsibilities:
- Design, develop, and maintain robust data pipelines using Azure Data Factory and Databricks.
- Build and optimize data flows and transformations for structured and unstructured data.
- Develop scalable ETL/ELT processes to extract data from various sources including SQL, APIs, and flat files.
- Implement data quality checks, error handling, and performance tuning of data pipelines.
- Collaborate with data scientists, analysts, and business stakeholders to understand data requirements.
- Work with Azure services such as Azure Data Lake Storage (ADLS), Azure Synapse Analytics, and Azure SQL.
- Participate in code reviews, version control, and CI/CD processes.
- Ensure data security, privacy, and compliance with governance standards.
Required Skills & Qualifications:
- 4–8 years of experience in Data Engineering or related field.
- Strong hands-on experience with Azure Data Factory and Azure Databricks (Spark-based development).
- Proficiency in Python, SQL, and PySpark for data manipulation.
- Experience with Delta Lake, data versioning, and streaming/batch data processing.
- Working knowledge of Azure services such as ADLS, Azure Blob Storage, and Azure Key Vault.
- Familiarity with DevOps, Git, and CI/CD pipelines in data engineering workflows.
- Strong understanding of data modeling, data warehousing, and performance tuning.
- Excellent analytical, communication, and problem-solving skills.
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