Senior Data Engineer
3 months ago
Job Description :
Key Responsibilities :
Data Engineering & Development :
- Design, develop, and maintain scalable data pipelines using Azure Databricks.
- Write and optimize PySpark code for processing large datasets.
- Implement ETL processes to ingest and transform data from various sources.
Data Management :
- Develop and maintain Delta Lake tables for efficient data storage and retrieval.
- Ensure data quality and integrity through rigorous testing and validation processes.
- Manage and optimize data workflows in Databricks for performance and cost-efficiency.
Collaboration & Communication :
- Work closely with data scientists, analysts, and business stakeholders to understand data requirements and deliver solutions.
- Participate in design and code reviews to maintain high development standards.
- Document data processes, pipeline designs, and best practices.
Azure Integration :
- Integrate Databricks workflows with other Azure services such as Azure Data Lake Storage, Azure SQL Database, and Azure Data Factory.
- Monitor and troubleshoot data pipelines, ensuring reliable and consistent data availability.
Continuous Improvement :
- Stay up-to-date with the latest developments in Azure Databricks and PySpark.
- Identify opportunities to improve data processing efficiency and reduce operational costs.
- Implement best practices for data engineering and contribute to the team's knowledge base.
Required Skills and Qualifications :
Technical Skills :
- 5+ years of experience in data engineering or a related field.
- Extensive experience with Azure Databricks and PySpark.
- Strong proficiency in SQL for data manipulation and querying.
- Experience with Delta Lake and data versioning.
- Knowledge of Azure Data Lake Storage, Azure Data Factory, and other Azure services.
- Proficiency in programming languages such as Python or Scala.
Professional Skills :
- Excellent problem-solving and analytical skills.
- Strong communication and collaboration skills.
- Ability to work in a fast-paced, dynamic environment.
Preferred Qualifications :
- Experience with Databricks MLflow for machine learning workflows.
- Knowledge of data warehousing concepts and solutions such as Snowflake or Azure Synapse Analytics.
- Familiarity with CI/CD pipelines and version control systems like Git.
- Experience in Agile development methodologies.
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