Data Engineer
4 weeks ago
Key Responsibilities :
- Build and maintain scalable data pipelines using PySpark on Azure Databricks.
- Develop ETL/ELT workflows in Azure Data Factory (ADF) to integrate data from diverse sources.
- Write optimized SQL queries for data transformation and validation.
- Collaborate with data analysts, scientists, and business teams to understand data needs.
- Monitor and troubleshoot performance issues in data workflows.
- Maintain data integrity and ensure adherence to data governance and security policies.
- Implement best practices for version control, testing, and deployment of data pipelines.
Required Skills :
- 24 years of professional experience in Data Engineering.
- Strong programming skills in Python and PySpark.
- Hands-on experience with Azure Databricks and ADF.
- Expertise in SQL (T-SQL or Spark SQL) for data wrangling and transformation.
- Understanding of data lake architecture and data warehousing concepts.
- Experience with version control tools (e.g., Git) and Agile/Scrum methodologies.
- Good understanding of structured and semi-structured data formats (CSV, JSON, Parquet, etc.)
Preferred Skills (Good To Have) :
- Experience with Delta Lake or Lakehouse architecture.
- Knowledge of Azure Synapse, Azure Data Lake Storage (ADLS).
- Familiarity with CI/CD pipelines using Azure DevOps.
- Basic understanding of dbt, Airflow, or other orchestration tools.
- Exposure to monitoring and logging tools (e.g., Azure Monitor, Log Analytics).
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