Description

You will design and implement enterprise-scale data platforms and AI solutions.

Responsibilities

• Build repeatable and reusable frameworks for data and AI solutions using AWS or Databricks.
• Design and manage Data Warehouses, Data Lakes, and complex data modeling architectures.
• Implement data quality and observability solutions across the enterprise.
• Deploy near real-time and streaming IoT solutions.
• Optimize EMR performance by fine-tuning Spark configurations and runtime.
• Integrate applications using APIs and microservices.

Required Skills

• 12+ years of experience in enterprise architecture with a focus on data platforms.
• 5+ years of hands-on experience with AWS Data and Analytics tools (S3, Glue, Athena, Lake Formation, EMR, Redshift, Kinesis, OpenSearch) or Databricks.
• 5+ years of experience in Data Warehouses, Data Lakes, and data modeling.
• 5+ years of coding experience with Python, Spark, R, or SQL.
• 3+ years of experience implementing data quality and observability solutions.
• 3+ years of experience with near real-time and streaming IoT solutions.
• 3+ years of experience in application integration, APIs, and microservices.
• 3+ years of experience in Data Science, Statistics, Machine Learning, and GenAI.
• Proficiency in Databricks for data engineering and analytics workloads.
• Strong knowledge of cloud-centric architecture and data sharing capabilities.
• Experience working within Agile methodologies.

Key Skills

Education

Any Graduate