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8 hours ago
We're seeking an experienced Big Data Solutions Architect to lead our data engineering team at a global technology company.
About the Role:- Big Data Pipeline Development: Design, develop, and maintain scalable, high-performance data pipelines and ETL processes on Databricks to ensure efficient data processing and storage.
- Data Architecture: Lead the architecture and implementation of secure, high-performance data solutions that meet business requirements.
- Cross-Functional Collaboration: Work with cross-functional teams, including business stakeholders, data scientists, and analysts, to gather requirements and deliver actionable data solutions.
- Optimization: Optimize data workflows for performance, cost-efficiency, and reliability, ensuring data quality and integrity.
- Data Integration: Integrate data from multiple structured and unstructured sources into Delta Lake and cloud data warehouses.
- Tech Leadership: Mentor junior engineers and provide technical leadership in data engineering best practices.
- Troubleshooting: Troubleshoot and resolve issues in data pipelines, ensuring high data availability and integrity.
The ideal candidate has hands-on experience in Databricks production environments, a deep understanding of modern data architecture, and a strong background in data engineering.
Requirements:- 6-7 years of experience in Data Engineering.
- Proven Subject Matter Expertise in Databricks (including Databricks SQL, Delta Lake, and MLflow).
- Strong experience with PySpark, Spark SQL, and Scala.
- Hands-on experience with cloud platforms (Azure preferred; AWS/GCP a plus).
- Proficiency in data modeling, ETL development, and data warehousing concepts.
- Solid understanding of big data ecosystems (Hadoop, Kafka, etc.).
- Strong SQL development skills with a focus on performance tuning.
- Experience in implementing CI/CD pipelines for data solutions.
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