Headline

Data & Platforms Engineer @ Zynix.Ai | Ex - Tredence |IIT Ropar |Databricks Certified | Python . Spark

About

Hi, I'm a Software Engineer passionate about crafting large-scale backend systems, modernizing data platforms, and designing architectures that not only work — but scale beautifully. My mission is simple: build resilient, real-time, and efficient systems that power smarter decisions and better experiences. I’ve helped modernize OLAP systems by migrating critical banking workloads from Synapse and Oracle to Databricks, building seamless data pipelines connected to real-time reporting layers like Power BI. Along the way, I also built a Flask accelerator that automated T-SQL to Databricks SQL conversion — boosting DDL migration efficiency by 80%, and cutting manual effort drastically. In the backend world, I architect microservices ecosystems with Spring Boot, Kafka, Redis, MySQL, MongoDB, and Docker, pushing towards Kubernetes-based scalable deployments. Real-time systems? I’ve optimized Socket.IO communication using Redis Pub/Sub and built fault-tolerant messaging architectures behind load balancers like HAProxy. 🌟 What I Bring: Data Engineering (ETL pipelines | OLAP Modernization | Databricks | Cloud-native Data Stacks) Backend Engineering (Microservices | Event-driven Systems | System Design) Real-Time Systems (WebSockets | Pub/Sub Architectures | High Availability Engineering) Scalability | Resiliency | Performance Optimization When I'm not engineering solutions, you’ll find me solving DSA problems for fun (already reached 1000 mark) and diving deep into Low-Level and High-Level Design to sharpen my system-building skills. Let’s connect if you’re passionate about building scalable systems, love a good tech puzzle, or just want to trade ideas about backend engineering and data architecture!

Location

Bengaluru

AI stack

claude

codex

cursor

gemini

github copilot

openai

Work experience

Data Engineer at Zynix.AI, Aug 2025 - Present · 1 yr 2 mos, Bengaluru, Redesigned the Quality Measures Dashboard data architecture, restructuring core Gold-layer consuming tables and optimizing 40+ downstream queries, reducing dashboard load time from 2 minutes to 55 seconds (54% reduction) while improving consistency and reliability of quality reporting. Built the Databricks CI/CD deployment framework from scratch using Databricks Asset Bundles, migrating 40+ jobs and pipelines from UI-managed, non-versioned workflows to Git-managed, configuration-driven deployments across Dev, UAT, and Prod, with environment-specific catalogs, schemas, and storage paths. Modernized L1→L2→L3 data processing by replacing legacy truncate-and-load patterns and history-table dependencies with incremental Delta Lake merge architecture, while developing reusable class-based Python/PySpark ETL components for schema reconciliation, hash-based deduplication, parameterized processing, and standardized read/write operations across healthcare data, improving data consistency, runtime efficiency, and maintainability. Implemented healthcare data integrations and modernization workflows including Labcorp, Quest, eClinicalWorks (eCW), ADT, and HL7 data, including enhancement of HL7 processing to Parquet on Databricks and development of Bronze-to-Mart transformation pipelines for downstream quality and population-health analytics. Enhanced and optimized provider and member data pipelines across L3 and downstream layers, strengthening merge, transformation, enrichment, validation, and exclusion-processing workflows across claims, demographic, provider, and ADT datasets; performed root-cause analysis and production remediation to improve data completeness, consistency, integrity, and reliability for healthcare analytics and quality reporting.

Data Engineer at Tredence Inc., Aug 2024 - Jul 2025 · 1 yr, Bengaluru

Software Engineer at Tredence Analytics, Aug 2024 - Jul 2025 · 1 yr, Contributed in a Flask-based accelerator to convert T-SQL to Databricks SQL, achieving 80% efficiency for DDLs and reducing manual effort. Migrated OLAP objects (tables, views, stored procs) from Synapse/Oracle to Databricks, unifying the data infrastructure. Reengineered complex Informatica mappings into Databricks Jobs and executed historical data loads using PySpark and Delta Lake. Improved ETL performance by 20% through query optimization and pipeline tuning, enabling faster Power BI reporting. Followed Agile methodology with CI/CD pipelines, version control using Git, and project tracking via JIRA.

Machine Learning Engineer at iHub - AWaDH @ IIT Ropar, Aug 2023 - Jan 2024 · 6 mos, Remote, Ingested and processed real-time IoT sensor data ( 60K+ data points/day) into AWS S3 using ETL pipelines built with AWS Lambda. Designed and trained ML models using scikit-learn, leveraging ensembling, stacking, and voting techniques to optimize performance on time-series sensor data, achieving prediction accuracy 70%

Software Developer at Ravikiran Infotech, Jun 2023 - Jul 2023 · 2 mos, Remote, - Contributed in Implementing Face Recogniton Feature in ODOO attandence Module for the Client.

Education

Bachelor of Technology - BTech, Electrical and Electronics Engineering, Indian Institute of Technology, Ropar

High school, Christ jyoti senior secondary school, Singrauli(M.P.)

Public links

github: https://github.com/ritesh027

leetcode: https://leetcode.com/riteshgupta0cam