
Data Engineer
4 weeks ago
We are looking for an experienced Data Engineer with strong expertise in Databricks and Azure Data Factory (ADF) to design, build, and manage scalable data pipelines and integration solutions. The ideal candidate will have a solid background in big data technologies, cloud platforms, and data processing frameworks to support enterprise-level data transformation and analytics initiatives.
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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