Giri Ramanathan

• Lead U.S. & LATAM Technical Solutions Engineering organizations focused on Spark, ML, GenAI, and cloud-native data platforms, driving measurable customer and business impact. • Build and scale AI-first support engineering teams that diagnose and debug complex customer issues using Databricks-native capabilities (Genie, AgentBricks) and evolve them into full-stack, enterprise-grade applications. • Lead AI-driven insights across NSAT, MTTM, MTTR, and SLOs, converting signals into actionable intelligence that accelerates resolution and improves customer experience. • Stay hands-on in Data & AI, building and scaling production-grade GenAI applications that materially improve productivity, operational efficiency, and cost structure. • Design and operationalize POC-to-production AI frameworks using Databricks Mosaic AI, LlamaIndex, vector databases (Pinecone, FAISS), agentic RAG architectures, and Databricks Apps. • Drive AI-powered platforms for case intelligence, product group labeling, automated case reviews, supportability insights, backlog optimization, and master case data management using Meta Llama models, Vector Search, and RAG. • Drive data-informed strategic initiatives aligned to revenue growth, cost optimization, and global operational excellence. • Serve as an advocate for field engineering and sales, strengthening cross-functional collaboration and execution. • Build trusted, long-term customer partnerships that drive adoption and success. • Establish strong operating models, mentor future leaders, and partner closely with R&D to enhance service offerings and streamline end-to-end supportability workflows.

* Lead the Americas Technical Solutions Engineering teams (Spark and Cloud) across the US, Brazil, and Costa Rica. * Spearheaded the launch of the LATAM Spark and cloud Tech Solutions Engineering team in Brazil and Costa Rica respectively, personally sourcing and screening over 2,000 profiles, performed market analysis on the comp and labor market in Brazil and managing the entire recruitment pipeline. * Onboarded teams in the US and Costa Rica, achieving multimillion-dollar cost savings and unlocking new opportunities for US support teams. * Conducted extensive market analysis and developed a competitive compensation strategy for Spark roles in Brazil, ensuring talent pool depth for this specialized skill set. * Established and re-built the India organization, including leadership development and organizational structure. * Led Databricks/Arcion Acquisition and migrated their support to Databricks support model * Delivered high-impact, revenue-generating initiatives, including Low-Cost Support, PAYG Support, Field POC Support, and the Tech SME program, in collaboration with Field Engineering and R&D teams. * Drove strategic partnerships with Microsoft and GCP for the Technical Solutions organization. * Maintained a 95% Brickster Leadership Index. * Developed a data-driven Supply/Demand model for the Americas organization, optimizing staffing requirements and successfully through DB SQL dashboards * Contributed to key Hackathon projects: LLM-based Case Complexity Framework, Customer Sentiment Analysis from call recordings, First Response Bot, and a Support Handbook Bot.

* Global lead for Spark Solutions team. * Set up our APJ operations for Spark Solutions Engineering, Cloud Support teams, Technical Incident Management team, Resident Solutions Engineering teams as part of our Customer Success org. * Built a top-performing team of 35+ in Spark, Cloud Platform support, IMs, and RSE/RSAs in APJ region. * Responsible for the growth of Spark/ML/AI Solutions & Consulting team(s) in the APAC region. * Responsible for hiring, retaining, and setting up high-performance diverse teams on customer-facing Big data architects, Consultants, Developers, Solutions Engineers (Spark and Cloud Platform) at various levels. * Lead the process of setting up an office space for Databricks India * Lead campus hiring for the fresh graduates hiring with the major engineering colleges in India. * Lead the strategic planning in hiring, Onboarding, Recruiting, Mentoring, and multiple initiatives in this region. * Created Spark TSE team as an investment pool in India for customer success org's growth. * Lead Technical team of Spark Solutions Engineers in APAC and taking care of Org KPIs, ROI, etc. * Leading Data Engineering and Data Science projects that help to improve team efficiencies and productivity. * Developing tools, innovations, and simplifying the complex tasks possible through Spark worldwide. * Job analyzer 2.0, Log Delivery 2.0 are few of the most successful projects/product features developed under my leadership. * Building Spark SME teams globally and top-notch Spark Engineers in the APAC region as a foundation.

* Lead team of bright Spark/ML/AI Engineers in the Technical Solutions area across the globe. * Lead the effort of Spark Innovations and Data Engineering projects. * Lead the project deliverables, timelines and implementations for our strategic customers across the globe. * Being a Technical Lead for the US team, I am responsible for SME team building in Spark/AWS/Azure areas, hiring, on-boarding, training and mentoring the team members in Spark, AWS, Azure technologies. * Provide mentorship to junior engineers, cross-functional teams and help them develop expertise in Databricks solutions. * Build, develop and implement strategies, processes, expertise, various big data automation tools and data pipelines for organization's internal data engineering and data science projects. * Training and Enablement with Sales, Engineering, Product Management, Global Support and Global Customer Success teams and work on various strategic initiatives.

* Employee Number ~ 70. Very first Engineer hired in our Customer Success Org. * Responsible for big data architecture, design, development, in-depth technical debugging, prod deployment, workflow orchestration, performance tuning, tools integration, machine learning, advanced analytics and data science projects for our top 5 strategic customers. * Strong hands on knowledge in most of the AWS and Azure cloud services. * Good hands on experience in data science workflow such as data preparation, applying mathematics and algorithms, automation and iterative processing for maximum accuracy in prediction, envisioning to large scale, Ensemble modeling and various modeling techniques in supervised/unsupervised/Reinforcement learning techniques. * Hands on skills in NLP, Image Processing in Python/Spark. * Coding in numpy, scikit-learn, Pandas, R for all Data Science projects and applied my skills on how to distribute them using Spark. * Strong understanding of ML, Neural networks and DL concepts and familiar with Keras, Tensorflow, Caffe, Theno, Pytorch libraries. * Strong experience in building Data Engineering, Data Science teams and to some extent DevOps team. * Deploy, Configure, Architect, Orchestrate, Test and Implement Kubernetes/Docker containerization apps, Prometheus Monitoring, Handing Persistent Volumes, Ansible playbooks.

* Lead a big data technical team of 10+ Engineers and made everyone successful in terms of their technical goals in Hadoop/ Spark * Contribution to the development of Saama's Fluid Analytics Engine - Product Development and RoadMap * First Big Data Developer in the organization and developed an end-to-end Enterprise Search Use Case @ CSAA. Have developed an entire Business Data Pipeline using Pig,Hive,MR and ElasticSearch Integration. * Have Architected and developed Auto Claims Fraud Analytics Application using MR/Hive/ElasticSearch Integration. Gartner has recognized us in the recent 2014 market guide for insurance fraud analytics. * Have Architected and developed Usage Based Insurance Application (Telematics Data) using Python,Flume,Java,Hive,ElasticSearch. * Have Architected and developed Enterprise Level Data Lake in just 3 months. Highly utilized Flume,GoldenGate and Hadoop EcoSystems. * Orchestrated and developed various Oozie jobs using WorkFlows, Co-Ordinators, Bundles and set up different prototypes to various projects. * Architected and Developed Home Owner Claims Fraud Analytics Application using Apache Spark-Core,Spark-SQL and Some Spark Streaming with Elastic Search. The new model reduced the fraud detection from 11 hours (Hadoop/MR/Hive) to 2 hours (Spark 1.6), thereby saving thousands of dollars every month for the business. * Played Advisory roles in designing and Building various Big Data architectures for multiple business customers. * Mentored and helped on building a scalable big data team.

• Responsible on Architecting and Developing Data Ingestion, Data Processing, Data Transformation process using Hadoop Ecosystems like Hive, Pig, MR, and Job Scheduling in Oozie. • Handled 2 TB of data volume and implemented the same in Production. • Supporting Hbase Architecture Design with the Hadoop Architect team to develop a Database Design in HDFS. Supported Map Reduce Programs those are running on the cluster. • Involved in HDFS maintenance and loading of structured and unstructured data. • DEVELOPED MapReduce jobs using customized Input File Formats, HCatInput Formats and other Java API. • Developed Hive queries and various collections transformations for data analysis to meet the business requirements. • Orchestrated Oozie workflow engines to run multiple Hive and Pig jobs. • Developed Hive queries to process the data and generate the data cubes for visualizing.

Worked as Software Consultant in companies such as * AT&T * EDS Telstra * Northern Trust Bank * WalMart Retail Stores * SallieMae Bank * Comerica Bank. Performed Multiple roles and responsibilities such as Mainframe Developer, Datawarehouse/ETL Developer, QA Lead, Hadoop Developer, etc.

Worked in the video card development of Trustix OS.

Pilani, Rajastan, India