Description

You will design and implement end-to-end cloud data architectures covering ingestion, processing, storage, governance, and consumption layers.

Responsibilities

• Architect scalable batch and real-time data pipelines using Spark, Databricks, or Kafka.
• Build secure cloud data ecosystems across AWS, Azure, or GCP while optimizing storage, compute, and cost.
• Define and enforce data governance frameworks including cataloging, lineage, quality, and cloud IAM security controls.
• Translate business, security, and engineering requirements into technical architectures.
• Create reference architectures, standards, and reusable frameworks while leading architectural reviews and capacity planning.

Required Skills

• 8–10 years of experience in data engineering or data architecture.
• 3+ years of experience in cloud-native architectures.
• Proven expertise in at least one major cloud platform (AWS, Azure, or GCP).
• Hands-on experience with cloud data services.
• Proficiency in distributed data processing using Spark or Databricks.
• Experience with event streaming and Kafka.
• Knowledge of data governance and security frameworks.
• Experience optimizing cloud resources for performance and cost.
• Bachelor’s or master’s degree in Computer Science, Information Technology, Data Engineering, or a related field.

Key Skills

Education

Any Graduate