Senior Data & AI Platform Engineer - Immediate Requirement

Key responsibilities:

·      Design and develop scalable backend systems using Python

·      Define and implement data architecture and database design strategies

·      Build and optimize data ingestion and transformation pipelines

·      Develop and maintain unified data models across multiple systems

·      Design end-to-end data flows and integration strategies

·      Collaborate with cross-functional teams to ensure efficient data handling and processing

·      Ensure system scalability, performance, and reliability

Machine Learning & AI Integration

·      Design and implement ML-enabled components (e.g., pattern detection, relationship mapping, anomaly detection) and integrate them into backend systems and APIs

·      Work with structured and unstructured data to support AI-driven insights, including data preparation, feature engineering, and pipeline development

·      Collaborate with AI/analytics teams to deploy, monitor, and optimize ML models within production environments

Core Technical Skills

·      Backend & System Design

·      Strong experience in Python development

·      Expertise in system scalability and performance optimization

·      Solid understanding of distributed systems and backend architecture

·      Data Engineering Concepts (VERY IMPORTANT)

·      Strong knowledge of data modelling (OLTP vs OLAP)

·      Understanding of data warehousing concepts

·      Experience with data lake architecture

·      Strong knowledge of REST APIs (Flask/Django/FastAPI)   · 

 Platforms (Highly Preferred)

Hands-on experience or strong understanding of:

·        Snowflake

·        BigQuery

·        Modern data lake systems

·  Data Ingestion & Processing

·       Ability to design and implement:

·       Data ingestion pipelines

·       Data transformation layers (ETL/ELT)

·       Unified and scalable data models

System Thinking & Architecture

Ability to: 

·       Design scalable backend architectures

·       Define and manage data flow across systems

·       Guide integration strategies between multiple services and platforms