Role Overview
We’re looking for a Data Platform Engineer to design and build scalable data models and enrichment pipelines that power analytics and AI-driven capabilities at Gradient Cyber.
This role sits at the intersection of data engineering, analytics, and security working closely with internal teams (detection engineering, automation, analytics) to deliver high-quality, intelligence-ready data.
While we leverage modern enrichment platforms like Fleak.AI, this role is best suited for someone who can quickly learn and adapt to new tools, rather than requiring prior experience with any specific platform.
What You’ll Do
Design and maintain unified, canonical data models across multiple data sources
Build and optimize data pipelines (ETL/ELT) for enrichment and transformation
Ensure data consistency, quality, and lineage across systems
Collaborate with cross-functional teams to support analytics, detection, and automation use cases
Improve data usability for AI, analytics, and operational workflows
Document data models, transformations, and enrichment logic clearly
Continuously enhance data reliability and platform performance
What We’re Looking For
2–3 years of experience in data engineering, analytics engineering, or data platform roles
Strong understanding of:
Data modeling and schema design
Data transformations and pipeline architecture
Hands-on experience with modern data tools or platforms (any ecosystem)
Exposure to security, log, or operational data
Ability to quickly learn new tools and technologies, especially in data enrichment and AI workflows
Strong problem-solving skills and attention to detail
Ability to work independently and manage multiple priorities
Transparent communication skills (written and spoken English)
Nice to Have
Experience with data enrichment platforms or AI-driven data systems (e.g., Fleak.A
📌 Data Platform Engineer (Bengaluru)
🏢 Gradient Cyber
📍 Bengaluru
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