
Data Engineering Leader
5 days ago
The Role
Data Engineering is a crucial component of our organization's data-driven strategy. We are seeking an experienced Data Engineer to lead the development and implementation of scalable data pipelines using Azure Databricks, Apache Spark, and Python.
Key Responsibilities:
- Data Pipeline Development: Design, build, and maintain large-scale ETL (Extract, Transform, Load) data pipelines that integrate structured and unstructured data from various sources into the cloud environment.
- Spark Optimization: Develop and optimize Spark jobs for efficient data processing on Databricks, leveraging distributed computing capabilities for optimal performance.
- Data Integration: Integrate data from relational databases, APIs, flat files, and other sources into the Azure cloud environment using Databricks and related tools.
- Collaboration with Data Scientists & Analysts: Work closely with data scientists, analysts, and business stakeholders to deliver robust data solutions that enable advanced analytics, machine learning, and reporting.
Required Skills & Qualifications:
- 3-5 years of hands-on experience in data engineering and working with Azure Databricks.
- Strong proficiency in Apache Spark, particularly in Databricks for building large-scale data pipelines and distributed data processing applications.
- Solid experience with Azure cloud services, including Azure Data Lake, Azure SQL Database, Azure Blob Storage, Azure Synapse Analytics, and Azure Data Factory.
Benefits:
- Opportunity to work on cutting-edge projects using latest technologies.
- Possible opportunities for professional growth and career advancement.
- A dynamic and collaborative work environment.
How To Apply:
Please submit your resume and cover letter through our online portal.
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