Senior Data & AI Platform Engineer

Job Description Roles & Responsibilities We are looking for a Senior Data & AI Platform Engineer with strong expertise in data architecture, database design, and scalable system development. The ideal candidate should have a deep understanding of data engineering concepts, modern data platforms, and the ability to design robust, scalable backend systems and data pipelines. Key Responsibilities: Key Responsibilities Design and develop scalable backend systems 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 Work closely with the AI/ML team to understand data requirements for model training, feature engineering, and pipeline development Prepare, validate, and deliver clean, structured data to support AI/ML systems and intelligent workflows Consume and integrate outputs from ML models into data pipelines and backend systems Maintain awareness of ML concepts to effectively collaborate with AI/analytics teams Core Technical Skills Backend & System Design Expertise in system scalability and performance optimization Solid understanding of distributed systems and backend architecture Data Engineering Concepts (IMPORTANT) Strong knowledge of data modelling (OLTP vs OLAP) Strong knowledge of data lake architecture (primary) and data warehousing concepts Strong knowledge of REST APIs and API design (FastAPI / Flask / Django) Core Platforms & Technologies (Required) Strong working knowledge of: Relational databases - strong hands-on experience required (e.g. PostgreSQL, MS SQL Server, MySQL) Non-relational / NoSQL databases - working knowledge required (e.g. MongoDB, SQLite, TimescaleDB, Redis) Graph databases - understanding of graph data models (e.g. Apache AGE, Neo4j concepts) Comfortable working across multi-database environments - relational, time-series, graph, and cache layers in a single architecture Good to Have: Hands-on experience with modern data tools such as Kafka, Airbyte, S3/ADLS, Snowflake, or similar platforms 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 Good to Have Experience with cloud platforms (AWS / GCP / Azure) Exposure to real-time data processing systems Knowledge of ML data pipelines or analytics workflows Experience using Python for data ingestion pipelines, transformation scripts, and automation workflows is an advantage What We're Looking For Passion for experimenting with new tools, frameworks, and ideas Ability to quickly prototype and iterate on features Interest in blending creativity with engineering Comfort working in less rigid, exploratory development environments Strong curiosity and self-learning mindset Bonus Points If You Use AI-assisted coding tools (like GitHub Copilot, Cursor, Antigravity, Claude) Build side projects, prototypes, or experimental apps Enjoy rapid MVP development, or creative coding Stay updated with latest trends in AI, and developer tools Desired Candidate Profile Requirements (Qualifications/Experience/Competencies) Bachelor's degree in Computer Science, Information Technology, Software Engineering, Data Science, or a related field. A Master's degree in a relevant field is an advantage 5 - 7 years of experience Company Industry IT - Software Services Department / Functional Area IT Software Keywords Senior Data & AI Platform Engineer Get real-time job updates only on our App