
Data Engineering Lead
1 day ago
We are seeking an experienced Data Engineering Lead to join our team and help build scalable, high-performance data solutions.
About the Role:
The ideal candidate has hands-on experience in Databricks production environments and a deep understanding of modern data architecture. They will design, develop, and maintain data pipelines and ETL processes on Databricks, leading the architecture and implementation of scalable, secure, and high-performance data solutions.
- Key Responsibilities:
- Collaborate with business stakeholders, data scientists, and analysts to gather requirements and deliver actionable data solutions.
- Optimize data workflows for performance, cost-efficiency, and reliability.
- Integrate data from multiple structured and unstructured sources into Delta Lake and cloud data warehouses.
- Implement best practices in data governance, security, and quality management.
- Mentor junior engineers and provide technical leadership in data engineering best practices.
- Troubleshoot and resolve issues in data pipelines, ensuring high data availability and integrity.
Required Skills & Experience:
- 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.
Benefits:
This role offers a competitive salary and benefits package, as well as opportunities for professional growth and development.
Others:
The company is committed to providing a positive and inclusive work environment, with a diverse team of professionals who share a passion for innovation and excellence.
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