Help & Supportcareers@gravityer.com
Data Engineer with 2+ years in ETL/ELT pipelines, AI systems & Cloud platforms.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Results-driven Data Engineer with 1.6+ years of experience designing scalable ETL/ELT data pipelines, CI/CD workflows, Agentic Al systems, and GenAl applications on AWS and Azure. Proficient in Python, PySpark, SQL, Databricks, Delta Lake, FastAPI, Docker, and GitHub Actions. Delivered 30-45% pipeline latency reduction, 60% faster query execution, and 99%+ data quality SLAs on 500 GB+ datasets. Collaborative team player with strong communication skills across cross-functional environments in e-commerce, telecom, and enterprise data domains.
Oriental Institute of Science and Technology, Bhopal
B.Tech · Information Technology
August 1, 2018 – June 30, 2022
Engineer Master Solutions
Data Engineer (Contract)
June 1, 2025 – June 1, 2026
Indore, Madhya Pradesh, India
Zingmind Technology
NLP and Data Pipelines Intern
September 1, 2024 – December 1, 2024
Indore, Madhya Pradesh, India
Cognizant Technology Solutions
Programmer Analyst Trainee
October 1, 2022 – May 1, 2023
Pune, Maharashtra, India
Agentic AI Customer Support System
October 1, 2023 – September 1, 2024
Built production-grade multi-agent AI system with FastAPI gateway routing customer queries to 5 specialised sub-agents: FAQ, Order, Refund, Billing, and Escalation, reducing average query resolution time by 35%. Implemented waterfall LLM cascade (Gemini 2.0-flash to fallback models) for fault-tolerant AI responses; deterministic Python policy engine prevents LLM hallucinations. Engineered hybrid Redis session store (Redis primary plus in-memory fallback) with 1-hour TTL, ensuring zero-downtime conversation continuity across concurrent multi-user sessions.
View ProjectGenerative AI Product Content Automation
October 1, 2023 – September 1, 2024
Built end-to-end GenAI pipeline auto-generating product titles, descriptions, SEO keywords, hashtags, and social captions from product images using Gemini Vision API. Delivered self-serve Streamlit UI enabling non-technical marketing teams to produce complete social media content packages in seconds, eliminating manual content creation for 100+ SKUs.
View ProjectQCall and PreCall AI Data Pipeline System
October 1, 2023 – September 1, 2024
Designed and deployed end-to-end ETL pipelines processing 100,000+ daily voice and text records, reducing data delivery lag by 45% and enabling near-real-time analytics. Integrated Hugging Face transformer models for intent detection and call data extraction, boosting classification accuracy by 25% over rule-based systems. Engineered LLM-powered RAG pipeline with STT (speech-to-text) transcription and TTS (text-to-speech) response generation, enabling intelligent pre-call scripting and post-call summarisation stored in Snowflake.
AWS Cloud Practitioner
Unknown
June 1, 2026 – Present
Python for Data Science
IBM
June 1, 2026 – Present
Data Analytics
Accenture
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, particularly in Agentic AI and Generative AI, alongside their core data engineering experience, indicates a strong alignment with innovative and forward-thinking teams. Their experience in cross-functional collaboration and stakeholder communication suggests they can integrate well into team environments. The breadth of skills across data engineering, AI/GenAI, DevOps, and cloud platforms points to a versatile individual who can adapt to various technical challenges and contribute broadly.
Soft Skills & Operational Fit
The candidate demonstrates strong soft skills such as cross-functional collaboration, stakeholder communication, and agile teamwork, as evidenced by project descriptions and professional experience. Their ability to work across diverse data domains (e-commerce, telecom, enterprise) and deliver quantifiable results (e.g., latency reduction, query execution time improvement) indicates a results-driven and operationally effective mindset. The self-directed upskilling in GenAI and cloud-native data engineering also highlights proactivity and a continuous learning attitude.