Jinesh Ranawat - Professional Portfolio

Cost Savings

$1.7M

Daily Data Processed

500TB

Team Leadership

2 → 50+

Leadership Awards

17

Leadership Development(Bp Advanced FLL) & Industry Influence

My Vision & Aspirations

"To democratize data engineering excellence and create systems that empower everyone to harness the full potential of data, regardless of their technical expertise."

Revolutionizing Pipeline Development

I'm leading BP's data engineering monorepo initiative using Bazel for build optimization. Our one-click pipeline generation system has reduced development time from weeks to hours, enabling engineers to create complex transformation pipelines with minimal manual coding. This system now supports over 10,000 pipelines with 99.9% reliability across multiple business units.

Accelerating Data Engineering

I've architected a suite of data engineering accelerators providing a 360-degree view of technical assets and data products. These accelerators integrate with ServiceNow for seamless workflow management and include pre-built templates for common tasks. The platform has reduced implementation time by 40% while improving quality and consistency, resulting in estimated savings of $2.5M annually.

AI Innovation & Democratization

I'm leading the development of advanced AI systems using Ollama and fine-tuning deepseek and llama models to create domain-specific AI assistants. These systems can be deployed on standard laptops, democratizing access to advanced AI capabilities. My current focus is making data more accessible through conversational interfaces that allow non-technical users to interact with complex data systems through natural language. My innovations include AI agents that automate routine data engineering tasks, provide intelligent suggestions for pipeline optimization, and reduce the expertise barrier for new team members.

Building Knowledge Libraries

I've created a comprehensive 'recipe library' of data engineering patterns and best practices, enabling teams to tackle common challenges with proven solutions. This standardized approach has improved code quality, reduced technical debt, and accelerated onboarding of new team members. The library continues to grow as we discover new efficient patterns.

About Me

I'm a Staff AI/Data Engineer with over 10 years of experience across financial services, fintech, and energy sectors. Currently at BP, I lead innovative data engineering initiatives, building multi-modal conversational AI agents and managing highly scalable, cost-efficient platforms across AWS/Azure.

My expertise spans cloud architecture optimization, real-time data processing, and team leadership. I've successfully built and scaled a data engineering team from 2 to 50+ engineers while maintaining zero escalations and 90% team satisfaction. As a passionate educator, I also work as a freelance consultant and trainer, sharing knowledge through well-crafted technical content and training sessions that have reached over 300 professionals.

Featured Projects View All

Geospatial Analytics Platform

Real-time vessel tracking with millisecond performance

Python Spark Azure GeoJSON

Developed a real-time geospatial tracking system enhancing safety across BP assets. The platform processes vessel location data with millisecond performance, providing critical insights for offshore operations and safety monitoring.

LOC8 Data Discovery

Pattern-based data discovery system

Java Spring Boot Neo4j React

Engineered a revolutionary pattern-based data discovery system that significantly improved data accessibility and usability across the organization. The system leverages machine learning techniques for intelligent pattern recognition and metadata management.

ADL Lineage with Neo4J

Data lineage and monitoring solution

Neo4j Python GraphQL D3.js

Implemented a comprehensive data lineage and monitoring solution using Neo4j, enabling full visibility into data flows and transformations. The solution helps in regulatory compliance, impact analysis, and data governance.

Azure Storage Optimizer

Cost optimization for cloud storage

Python Azure PowerShell Terraform

Developed an innovative solution that saved millions in Azure storage costs by optimizing data lifecycle management, implementing intelligent tiering, and automating cleanup of redundant data while maintaining data integrity and access requirements.

TensorFlow Deep Learning

Advanced Deep Learning Implementation

TensorFlow Deep Learning Neural Networks Python

Comprehensive guide to TensorFlow implementation, covering neural network architectures, model optimization, and real-world applications. Includes detailed methodology and best practices for deep learning projects.

Technical Writing View All Articles

Demystifying Spark Resource Calculation

Aug 13, 2024

Have you ever felt like you're playing a guessing game when allocating resources for your Apache Spark jobs? You're not alone...

Forward Deployed Engineers: Building AI Systems

Feb 6, 2024

In the rapidly evolving landscape of artificial intelligence, a new role has emerged that bridges the gap between cutting-edge AI...

How 103 Lines of Code Saved Millions on Azure Storage

Apr 22, 2024

As businesses grow and data accumulates, the costs associated with storing and managing that data can quickly escalate...

Staff AI/Data Engineer

BP | November 2024 - Present

Building multi-modal conversational AI agents and managing highly scalable platform services
Accelerating adoption of AWS EMR, Iceberg, Glue, Azure Databricks, and Generative AI
Leading cloud cost optimization initiatives, achieving $2M in savings for 2024
Building a strong Data Engineering developer community across the organization

Data Engineering AI Tech Lead

BP | December 2021 - Present

Led a federated team of 25+ data engineers supporting 30+ critical P&O products
Developed real-time geospatial systems with millisecond performance
Implemented cost optimization strategies reducing cloud costs from $50K to $7K monthly
Delivered projects across Asset Intelligence, Production, SIRIUS, Digital Twin, and Geospatial
Received 17 leadership awards across technical excellence, leadership, and team development

Associate Director

UBS | August 2020 - September 2021

Led cloud and big data technology for Transaction and Reference data Reporting in IB...

Assistant Vice President

Barclays Investment Bank | March 2015 - August 2020

Led big data development for Market Risk VaR calculation using Hadoop ecosystem...

Senior Subject Matter Expert

Amdocs | May 2014 - March 2015

Led core framework development in R&D and business application development for Amdocs Ordering...

Software Engineer

Accenture | June 2012 - May 2014

Developed multi-channel applications for Barclays retail banking using Java and JavaScript MVC...

What Colleagues Say

I'm glad working closely with Jinesh for almost 3.5 years, and I'm truly impressed by his leadership qualities and approach to problem-solving. His skills in leadership, team management, and quick decision-making are outstanding. Jinesh creates a supportive and comfortable environment, allowing the team the freedom to excel.

Praveen Batta

Senior Engineer at Nagarro, former BP

Jinesh is a highly skilled professional who leverages his expertise in Azure, Palantir, and data modeling to simplify even the most complex concepts. His dedication to continuous learning and upskilling is evident in the way he stays ahead of industry trends and shares his knowledge through well-crafted blogs and insightful content.

Maanvitha Allampalli

API Engineer at Synchrony

I got a chance working with Jinesh and it was one of the greatest cooperations I had. He has experience in managing smaller and bigger teams. Moreover, he managed to build a team from scratch and expand it to almost 50 people. Due to his effective communication skills, conflict resolution, and technical knowledge, he is always able to deliver, while creating a positive atmosphere in the team.

Tamara Sente

Data Engineer

Jinesh is one of those exceptional talents, who will relentlessly deliver innovative and outstanding solutions to business/technical problems. His is an avid learner and always on the lookout to bring something new to the table. Jinesh can work on complex problems with minimal supervision and he has a knack to look at problems from different and often unique perspectives.

Shimant Das

Market Risk | Data, Analytics and Reporting

View All Recommendations

Technical Skills

Cloud Platforms (AWS, Azure)

95%

Data Engineering

98%

Python & Java

90%

Databricks, Spark

92%

Neo4j, Graph Databases

85%

CI/CD, DevOps (Bazel)

88%

Real-time Processing

94%

Generative AI & LLMs

90%

AI Model Fine-tuning

88%

Certifications

Azure Certified Architect

AZ-303 & AZ-304
Databricks Certified Data Engineer

Associate Level
Generative AI Fundamentals

Databricks Academy
Palantir Certified Professional

Data Integration Specialist

Professional Advisory & Community Engagement

On weekends, I provide professional advisory services to organizations and individuals in the areas of Site Reliability Engineering (SRE), cloud architecture, and data engineering. This focused engagement allows me to contribute to the broader technology community while sharing specialized knowledge across various industries.

Technical Advisory

SRE implementation for cloud-native applications
Data infrastructure reliability and optimization
Cloud architecture for enterprise workloads
ML/AI platform engineering
Data observability and governance frameworks

Provided strategic direction to multiple organizations implementing cloud-native architectures and SRE practices.

Knowledge Sharing

Architecture review sessions for technical teams
Technical mentoring for mid-senior engineers
Technical content development for organizations
Best practices implementation guidance
Performance optimization methodologies

Engaged with over 300 professionals through structured knowledge-sharing initiatives focused on practical implementation.

Community Initiatives

Mentor for FUEL NGO supporting technology graduates in career development
Technical advisor for early-stage startups in data infrastructure
Author of technical publications on Medium
Contributor to open-source data engineering projects
Advocate for cost-efficient cloud architectures and practices

Project Portfolio in Detail

Real-time Geospatial Vessel Tracking

Python Spark Structured Streaming Azure Event Hubs GeoJSON AIS Data Power BI

Problem:

BP needed a real-time monitoring system to track vessel movements near offshore platforms to enhance safety and operational awareness. Traditional tracking systems had significant latency issues (5-10 minutes), making them inadequate for safety-critical applications.

Solution:

Designed and implemented a high-performance geospatial tracking platform that ingests, processes, and visualizes AIS (Automatic Identification System) vessel data in milliseconds. The system provides real-time alerts for proximity violations and captures historical vessel trajectories.

Technical Implementation:

Built ingestion pipeline using Azure Event Hubs for AIS data from multiple providers
Implemented Spark Structured Streaming with Python for real-time data processing
Created geospatial functions for proximity calculations and trajectory analytics
Developed alert system for vessels approaching restricted zones or platforms
Designed dashboard for operational visibility using Power BI and custom visualizations

Impact:

Reduced vessel tracking latency from minutes to milliseconds
Improved offshore safety by providing proactive alerts for potential vessel collisions
System now monitors over 30,000 vessels daily across BP's global operations
Solution extended to Castrol division for supply chain optimization
Recognized with "Play to Win" award for technical excellence

LOC8 Pattern-Based Data Discovery System

Java Spring Boot Neo4j React Machine Learning GraphQL

Problem:

Data scientists and analysts struggled to discover relevant datasets across BP's vast data ecosystem, often requiring weeks to locate and understand data sources. This resulted in duplicated efforts and missed insights.

Solution:

Created LOC8, a revolutionary pattern-based data discovery system that catalogs, analyzes, and surfaces data assets based on usage patterns and semantic understanding. The system provides an intuitive interface for search, exploration, and data lineage tracking.

Technical Implementation:

Built data catalog and lineage tracking using Neo4j graph database
Implemented machine learning algorithms for pattern recognition and data classification
Developed Spring Boot microservices for metadata harvesting and processing
Created React frontend with advanced search and visualization capabilities
Designed GraphQL API layer for efficient data retrieval and updates

Impact:

Reduced data discovery time from weeks to minutes
Improved data governance and compliance through comprehensive lineage tracking
Enabled self-service data exploration for 500+ data consumers
Integrated with existing data catalogs and governance tools
Solution now tracks over 10,000 data assets across the organization

Azure Storage Cost Optimization Solution

Python Azure Blob Storage Azure Functions Terraform PowerShell

Problem:

BP was experiencing rapidly escalating Azure storage costs with petabytes of data in blob storage, much of which was infrequently accessed. Manual management of storage tiers was impractical at this scale.

Solution:

Developed an intelligent storage optimization solution that automatically analyzes access patterns, applies appropriate lifecycle policies, and transitions data between storage tiers while maintaining access requirements and compliance.

Technical Implementation:

Created Python scripts for analyzing blob storage access patterns
Developed intelligent algorithm for determining optimal storage tier based on access frequency
Implemented Azure Functions for automated tier transitions and cleanup operations
Built reporting dashboard for cost tracking and savings visualization
Deployed infrastructure-as-code using Terraform for consistent environment setup

Impact:

Reduced Azure storage costs by millions annually
Decreased hot storage usage by 60% through intelligent tiering
Automated blob lifecycle management for petabytes of data
Implemented solution across multiple business units
Featured in internal BP technical publications and shared as a case study

Featured on BP's Global Website

$1.7M

500TB

2 → 50+

17

My Vision & Aspirations

About Me

Featured Projects View All

Geospatial Analytics Platform

Key Achievements:

LOC8 Data Discovery

Key Achievements:

ADL Lineage with Neo4J

Key Achievements:

Azure Storage Optimizer

Key Achievements:

TensorFlow Deep Learning

Key Topics:

Technical Writing View All Articles

Demystifying Spark Resource Calculation

Forward Deployed Engineers: Building AI Systems

How 103 Lines of Code Saved Millions on Azure Storage

Professional Experience

Staff AI/Data Engineer

Data Engineering AI Tech Lead

Associate Director

Assistant Vice President

Senior Subject Matter Expert

Software Engineer

What Colleagues Say

Technical Skills

Certifications

Professional Advisory & Community Engagement

Technical Advisory

Knowledge Sharing

Community Initiatives

Project Portfolio in Detail

Real-time Geospatial Vessel Tracking

LOC8 Pattern-Based Data Discovery System

Azure Storage Cost Optimization Solution

Get In Touch