Anuj Sinha

About Anuj Sinha

Data Engineer and former AWS Cloud Support Engineer, specializing in enterprise-scale data architecture and cloud solutions. In an era of rapidly evolving technology, my greatest strength is the ability to quickly master new tools and frameworks – demonstrated through my journey from business analytics to cloud support engineering to data engineering at AWS.At AWS, I architect end-to-end data solutions that drive business transformation, including recent GenAI implementations using Amazon Bedrock that achieved 60% efficiency improvements. I excel at designing scalable data pipelines, optimizing data lakes, and implementing robust visualization solutions using AWS\'s comprehensive suite of services.My unique background as an AWS Cloud Support Engineer, where I resolved 650+ complex architectural and performance issues, has given me exceptional troubleshooting abilities and deep technical knowledge of analytics tools like Redshift, QuickSight, and Neptune. This experience taught me how to think at scale, architect for reliability, and effectively communicate complex technical solutions to diverse stakeholders.I bring a rare combination of:Deep technical expertise in data architecture and cloud technologiesProven track record of optimizing large-scale data systemsStrong customer-focused problem-solving skillsAbility to rapidly learn and implement emerging technologiesExperience mentoring teams and driving technical initiativesCurrently seeking Senior Data Engineer or Data Architect roles where I can leverage my expertise in building scalable data solutions while continuing to push the boundaries of what\'s possible with emerging technologies.Open to connecting with data architects, engineering leaders, and fellow cloud enthusiasts. Let\'s discuss building the next generation of data solutions!\"

Experience

1. Data Engineer

   Amazon Web Services (AWS)

   Feb 2022 — Present · Dallas, TX, US

   Developed an AI agent using AWS Bedrock agents and microservices to deliver real-time competitive intelligence, delivering content in Salesforce CRM under a multi-agentic AI system, reducing research time by 50% and enhancing AWS seller win rates.Engineered data pipelines to ingest Sales Plays content from Highspot into vector databases, used AWS Bedrock\'s Anthropic LLMs to recommend and summarize plays based on Salesforce opportunity details, accelerating Sales Play selection by 40%.Architected an end-to-end analytics solution, built real-time/streaming data pipelines with EventBridge, Lambda, Kinesis Firehose, and Glue for a partitioned S3 data lake, implemented data governance with Lake Formation to enable secure analytics for 10+ stakeholders.Developed fine-tuned prompts for Bedrock LLMs using prompt engineering best practices, leveraging RAG and instruction tuning to reduce hallucination by 30% and enhance response accuracy.Built a recommendation system for ProServ offerings, integrating AWS Glue and Redshift Spectrum pipelines to process S3 data, leveraging Bedrock LLMs for recommendations, boosting Salesforce revenue by 25% for select opportunitiesCrafted star schemas in AWS Redshift, integrating diverse sources for QuickSight BI reporting, optimized Redshift performance to achieve 40% faster queries and enable scalable, enterprise-grade analytics.Led Amazon QuickSight administration for enterprise analytics, crafted 50+ complex SQL datasets, created 30+ interactive dashboards, implemented RLS/CLS, embedded and migrated dashboards in applications.Implemented a TypeScript component for user impersonation in an AWS Application, enabling real-user issue resolution and accelerating resolution speed by 60% for enterprise applications.Designed fault-tolerant data ingestion frameworks supporting multiple data sources (APIs, databases, files, streaming) with built-in retry mechanisms and monitoring capabilities to ensure 99.9% data availability.

Education

• Rajasthan Technical University, Kota

  Bachelor of Technology (B.Tech.), Information Technology

  2008 — 2012

• The University of Texas at Dallas

  Information Technology and Management, IT/Internal Audit, business Intelligence, Data Analytics, IT consulting and Project Management

  2017 — 2019