
Databricks Data Solutions Architect
5 days ago
Data Engineering Leader
We are seeking an experienced Senior Data Engineer to fill this role. The ideal candidate will have a strong background in data engineering, with hands-on experience in Databricks production environments and a deep understanding of modern data architecture.
The successful candidate will be responsible for designing, developing, and maintaining scalable, high-performance data solutions using Databricks. This will involve collaborating with cross-functional teams to create robust data pipelines and ensuring the reliability, quality, and observability of data across platforms.
- Data Pipeline Development: Design, develop, and maintain data pipelines and ETL processes on Databricks to ensure efficient data processing and reliable data delivery.
- Technical Leadership: Lead the technical direction and implementation of scalable, secure, and high-performance data solutions using Databricks and cloud-based technologies.
- Cross-Functional Collaboration: Collaborate with business stakeholders, data scientists, and analysts to gather requirements and deliver actionable data solutions that meet business needs.
- Performance Optimization: Optimize data workflows for performance, cost-efficiency, and reliability using best practices in data governance, security, and quality management.
- Data Integration: Integrate data from multiple structured and unstructured sources into Delta Lake and cloud data warehouses to support data-driven decision-making.
- Tech Mentorship: Mentor junior engineers and provide technical leadership in data engineering best practices to ensure the success of the team.
Required Skills & Experience:
- 6-7 Years of Experience: 6-7 years of experience in Data Engineering with a proven track record of delivering large-scale data projects.
- Databricks Expertise: Proven subject matter expertise in Databricks (including Databricks SQL, Delta Lake, and MLflow) with hands-on experience in production environments.
- Cloud Platforms: Strong experience with cloud platforms (Azure preferred; AWS/GCP a plus) with a focus on scalability, security, and reliability.
- Data Modeling & ETL: Proficiency in data modeling, ETL development, and data warehousing concepts with a focus on data governance, security, and quality management.
- Big Data Ecosystems: Solid understanding of big data ecosystems (Hadoop, Kafka, etc.) with experience in integrating data from multiple sources.
About the Role:
This is an excellent opportunity to showcase your skills and contribute to the growth of our organization.
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