Description

You will lead the strategic migration of legacy data infrastructures into a modern, cloud-native data plane, defining architecture for scalable and future-proof systems.

This role is hybrid.

Responsibilities

• Design and execute multi-year strategies to migrate from legacy RDBMS and mainframes to modern Data Lakehouses and Data Meshes.
• Define the modern data plane architecture, integrating storage (S3/ADLS/GCS), compute (Spark/Snowflake/Databricks), and consumption layers.
• Architect robust patterns for data movement across hybrid and multi-cloud environments, ensuring minimal downtime and zero data loss.
• Create reusable blueprints for ELT/ETL pipelines, Change Data Capture (CDC), and real-time streaming using Kafka or Redpanda.
• Optimize cloud spend and query performance through advanced indexing, partitioning, and caching strategies.

Required Skills

• 10+ years of experience in data architecture and engineering.
• Deep expertise in ELT/ETL pipeline design and implementation.
• Hands-on experience with Spark, Snowflake, and Databricks.
• Proficiency in building real-time streaming architectures with Kafka or Redpanda.
• Experience architecting data planes optimized for Generative AI and LLM workloads.
• Strong understanding of hybrid cloud data strategies and security-as-code principles.

Preferred Skills

• Experience with vector databases and feature stores for AI/ML readiness.
• Familiarity with Iceberg/Hudi table formats and serverless data processing.

Key Skills

Education

Any Graduate