Senior Data Engineer
2 weeks ago
Responsibilities :
- Design, develop, and implement scalable data pipelines using Databricks and PySpark for data ingestion, transformation, and loading (ETL) processes.
- Develop and maintain data models that ensure data quality, consistency, and efficiency.
- Utilize SQL for data extraction, transformation, and analysis.
- Implement data integration strategies to seamlessly connect various data sources.
- Design and implement data architecture solutions to optimize data storage, processing, and access.
- Ensure data governance, security, and compliance by adhering to established policies and procedures.
- Monitor and optimize data pipelines for performance and scalability.
- Collaborate with data analysts, data scientists, and other stakeholders to understand data requirements and translate them into technical solutions.
- Document data pipelines and data models for clarity and maintainability.
- Stay up-to-date with the latest advancements in data engineering technologies and best practices.
Qualifications :
- 7+ years of experience in data engineering or a related field.
- Proficiency in SQL, data modeling techniques, and ETL tools.
- Strong knowledge of data integration, data migration strategies, and data architecture design principles.
- In-depth expertise in Databricks and PySpark for large-scale data processing.
- Solid understanding of data governance, data security best practices, and compliance regulations.
- Excellent problem-solving, analytical, and communication skills.
- Ability to work independently and as part of a cross-functional team.
- Strong attention to detail and a commitment to delivering high-quality work
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