Cloud Data Architect
1 month ago
We are seeking a highly skilled Cloud Data Architect to lead the design and implementation of large-scale, cloud-native data platforms using Databricks, primarily on AWS. You will work closely with data engineers, cloud architects, and business stakeholders to build efficient, secure, and scalable data solutions that drive key business insights.
Key Responsibilities:
- Architect and implement highly scalable data solutions and pipelines using Databricks on AWS.
- Integrate AWS data tools, including S3, Redshift, Glue, Athena, RDS, and Databricks for end-to-end data processing, analytics, and reporting.
- Design secure, high-performance data platforms that follow best practices for AWS architecture (networking, IAM, encryption, cost optimization).
- Leverage Databricks for advanced data transformation, ETL processes, and big data analytics.
- Optimize and monitor AWS-based Databricks environments for performance, cost, and scalability.
- Ensure data governance, security, and compliance requirements are met across data solutions.
- Collaborate with DevOps teams to implement CI/CD pipelines, automate deployments, and ensure smooth integration of Databricks into AWS infrastructure.
- Provide architectural leadership, technical direction, and best practices for leveraging cloud-native services.
- Lead the implementation of proof-of-concepts and production-ready systems, delivering high-quality data products on AWS.
Requirements:
- 8+ years of experience in data engineering, cloud architecture, or related fields.
- Mandatory expertise in AWS data tools: S3, Redshift, Glue, Athena, RDS.
- Strong experience with Databricks for data processing and analytics.
- Proficiency in SQL for data transformation and analysis.
- Strong knowledge of cloud architecture principles, AWS infrastructure, and best practices for scalability, security, and cost management.
- Hands-on experience building and deploying CI/CD pipelines in AWS environments.
- Excellent communication and collaboration skills to work with technical and non-technical stakeholders.
- Preferred: Experience with Azure data tools (Azure Data Lake, Azure Synapse, Data Factory)
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