Data Engineer
1 day ago
Job Description:
We are seeking a highly skilled and motivated Data Engineer with 45 years of hands-on experience in building scalable data pipelines and transforming complex datasets. The ideal candidate should have strong expertise in Azure Data Factory (ADF), Azure Databricks (ADB), Python, and PySpark, along with solid proficiency in SQL.
Key Responsibilities:
- Design, develop, and maintain robust data pipelines using Azure Data Factory and Azure Databricks.
- Write efficient and scalable code in Python and PySpark for data ingestion, transformation, and processing.
- Collaborate with data analysts, data scientists, and business stakeholders to understand data requirements and deliver solutions.
- Implement best practices in data modeling, data quality, and pipeline orchestration.
- Optimize existing workflows for performance, scalability, and cost-efficiency.
- Work with large volumes of structured and semi-structured data from multiple sources.
- Maintain and improve SQL-based ETL processes and ensure data accuracy and reliability.
Required Skills:
- 4–5 years of experience in Data Engineering or a similar role.
- Hands-on experience with Azure Data Factory (ADF) and Azure Databricks (ADB).
- Strong programming skills in Python and PySpark.
- Expert-level SQL skills for querying, analysis, and performance tuning.
- Experience working with large-scale data pipelines and distributed systems.
- Familiarity with Azure cloud services and data storage (e.g., ADLS, Blob Storage).
- Experience in debugging, testing, and version controlling data workflows.
Preferred Qualifications:
- Experience with CI/CD pipelines in data engineering projects.
- Knowledge of data governance, security, and compliance.
- Exposure to DevOps practices or tools like Git, Azure DevOps, etc.
- Familiarity with other Azure tools (e.g., Synapse, Logic Apps) is a plus.
Soft Skills:
- Strong problem-solving and analytical thinking.
- Effective communication and documentation skills.
- Ability to work independently as well as in a collaborative team environment.
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