Description

You will architect and implement end-to-end modern data solutions on AWS, focusing on cloud-native platforms for warehousing, BI, and analytics.

Responsibilities

• Design and deploy cloud-native data architectures using AWS services and advanced frameworks like Databricks.
• Lead end-to-end implementation of modern data solutions, including ETL/ELT pipelines and data management strategies.
• Collaborate with Data Engineering, Data Management, and BI teams to resolve performance challenges and define constraints.
• Architect columnar databases and cloud-native database solutions, ensuring scalability for varied data consumption needs.

Required Skills

• 15+ years of IT experience, with at least 4 years specifically implementing cloud-native data solutions.
• Deep expertise in AWS data services and cloud-native data platform architectures.
• Hands-on experience with Databricks for advanced data processing.
• Strong knowledge of ETL/ELT tools and data engineering principles.
• Proficiency with Kafka (Confluent) for data ingestion and streaming.
• Experience with NoSQL databases, specifically Key-Value and Document stores.
• Familiarity with Snowflake and other popular data warehouse technologies.

Preferred Skills

• Experience implementing analytic models using AWS SageMaker for production workloads.
• Knowledge of Data Mesh architecture and Data Product design.

Key Skills

Education

Any Gradute