Help & Supportcareers@gravityer.com
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Data Engineer with 3+ years in Python, SQL & Cloud Data Platforms
Data Engineer with 3+ years of experience designing, developing, and maintaining scalable Python-based ETL/ELT pipelines, REST API integrations, cloud data platforms, and enterprise reporting solutions within financial services environments. Strong expertise in Python, SQL, AWS, Snowflake, and cloud-based data integration, with hands-on experience developing automated data pipelines, transforming high-volume datasets, and supporting business intelligence reporting. Skilled in API integration, relational databases, data warehousing concepts, data quality, technical documentation, and stakeholder collaboration. Experienced in translating business requirements into reliable data solutions while delivering clean, maintainable, production-ready code using Agile development practices and Git version control.
Coventry University, UK
M.Sc. · Data Science
January 1, 2024 – January 1, 2025
HMSIT, India
B.Tech · Computer Science & Engineering
August 1, 2017 – July 1, 2021
Trinity Technolabs
Data Engineer
February 1, 2025 – Present
India
FIS
Software Engineer
October 1, 2021 – December 1, 2023
India
Netflix Data Analysis Using dbt
June 30, 2026 – Present
Designed and developed a modern cloud-based data platform using Amazon S3, Snowflake, SQL, Python, and dbt to process and transform 20M+ streaming records. Built production-style ETL pipelines following software engineering principles, modular design patterns, automated testing practices, and data engineering best practices. Developed modular dbt transformation pipelines using incremental models, SCD Type 2 snapshots, source freshness monitoring, and dependency-managed transformations. Designed dimensional data models utilizing fact and dimension tables to support analytical reporting and business intelligence requirements. Implemented 15+ automated data quality tests including uniqueness validation, null checks, referential integrity validation, and freshness monitoring. Optimized Snowflake warehouse performance through SQL query tuning and transformation optimization techniques, improving processing efficiency and reducing compute costs.
Comparative Analysis of Machine Learning Techniques for Heart Attack Prediction
June 30, 2026 – Present
Conducted structured requirements gathering sessions with healthcare stakeholders to identify analytical objectives, constraints, and success criteria. Evaluated Linear Regression, Naïve Bayes, SVM, and KNN algorithms using datasets containing 300+ patient records and 14 clinical attributes. Produced exploratory data analysis reports, feature importance assessments, model evaluation metrics, and analytical visualizations supporting model selection.
Smart Monitoring of Water Pumps: Machine Learning-Based Failure Prediction
June 30, 2026 – Present
Developed predictive maintenance models utilizing multiple machine learning algorithms across 10,000+ operational sensor records. Built data preprocessing workflows including feature engineering, PCA dimensionality reduction, and outlier detection techniques. Achieved 96.7% prediction accuracy and documented model validation metrics, cross-validation results, and deployment-readiness recommendations.
AWS Cloud Quest: Cloud Practitioner – Amazon Web Services (AWS)
Amazon Web Services (AWS)
June 1, 2026 – Present
Databricks Fundamentals
Databricks
June 1, 2026 – Present
Strategic Management and Leadership Practice (Level 7)
Unknown
June 1, 2026 – Present
BCG Data Science Job Simulation – Forage
BCG (Boston Consulting Group)
June 1, 2026 – Present
Develop Your Communication Skills and Interpersonal Influence - LinkedIn Learning
LinkedIn Learning
June 1, 2026 – Present
Excel Essential Training (Microsoft 365) – LinkedIn Learning
LinkedIn Learning
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, including academic projects in machine learning and data analysis, alongside professional experience in financial services, indicates a broad interest and adaptability. Their current role as a Data Engineer and previous role as a Software Engineer align well with the target role, demonstrating a clear career progression in data. The breadth of technical skills across various cloud platforms, databases, and BI tools suggests a willingness to learn and adapt to different technological stacks, contributing positively to cultural fit.
Soft Skills & Operational Fit
The candidate demonstrates strong soft skills through their emphasis on stakeholder collaboration, requirements gathering, and producing technical documentation. Their experience with Agile methodologies and CI/CD practices indicates a good operational fit for modern data engineering teams. The certifications in communication and leadership further support their potential for effective teamwork and problem-solving.