I build data platforms that work at scale and keep working as your business grows. Over the past 10 years I've served as the lead or founding data engineer across fintech, e-commerce, ride-hail, legal tech, and cybersecurity companies. That means I've designed systems from scratch, made architecture decisions with no one to fall back on, and delivered platforms that product teams actually use. Here's what I typically get hired to do: → Build greenfield data platforms on AWS or GCP from the ground up → Design and ship production ETL/ELT pipelines (Airflow, Dagster, dbt) → Set up scalable warehouses and governance (Snowflake, BigQuery, Redshift) → Implement real-time streaming pipelines (Kafka, Spark Streaming, CDC) → Build AI-powered data applications (RAG, LLMs, LangChain, vector DBs) → Fix broken or unreliable pipelines and make them production-grade → Architect cloud infrastructure on AWS, GCP, Azure (Terraform, Kubernetes) Recent work includes: - Led data platform engineering for a US e-commerce company processing billions of events daily. I re-architected ingestion pipelines, built Snowflake governance from scratch, introduced Prometheus monitoring and CI/CD standards across the platform. - Built a full data platform on GCP (BigQuery, Dataproc, Airflow) for a music streaming company. Firebase, AppsFlyer, and app store data all flowing into one warehouse within weeks. - Designed an AWS data platform for a ride-hail company managing 500+ streaming and 700+ batch jobs — including a self-serve portal that replaced multi-step CLI workflows for engineers. - Built a legal AI search engine using LangChain, Pinecone, and RAG — full pipeline from document ingestion to LLM-generated answers, deployed on AWS with auto-scaling. - Built an AI inventory insights agent for a US automotive company — multi-source data pipelines, real-time APIs, conversational interface. I work in English daily, communicate proactively, and deliver production- ready code — not prototypes. I'm used to working directly with CTOs and technical leads in US and European time zones. Tools I work with regularly: Python · SQL · Airflow · Dagster · dbt · Snowflake · BigQuery · Spark · Meltano · Kafka · AWS (S3, EMR, Glue, ECS, Lambda, EC2, EKS) · Databricks · GCP · Azure Terraform · Docker · Kubernetes · LangChain · FastAPI · MLflow · Weaviate, Celery If you're building a data platform, fixing one, or adding AI/ML capabilities to your stack, let's talk.

Hello, I’m Lenin Mishra, and I bring 10 years of expertise in designing and implementing modern data stack pipelines. Currently, I lead the analytics engineering team at a multinational bank with a presence in 6 countries. My specialization lies in the Modern Data Stack (MDS), which typically includes: 1. Fully managed ELT data pipelines such as Airbyte, Stitch, or Fivetran. 2. Columnar storage data warehouses like Redshift, Snowflake, or BigQuery. 3. Data transformation tools such as DBT. 4. BI tools like Tableau, Looker, or other data visualization platforms. 5. Orchestration services like Airflow or Dagster to manage and schedule workflows. If you’re looking for assistance in any of these areas, I’m here to help!

Founders usually bring me in when the product has outgrown its engineering. I help startups and growing companies architect, build, and scale AI platforms, financial infrastructure, trading systems, and enterprise SaaS products where reliability, scalability, and execution matter more than simply writing code. My role is rarely just backend development. I own technical architecture, engineering direction, production reliability, code quality, and delivery while remaining deeply hands-on with implementation. Over the past 9+ years I've helped founders build systems that process millions of events, support real-time decision making, integrate AI into production workflows, and move financial data safely and reliably at scale. What I Build AI Platforms & Agentic Systems - AI-native SaaS platforms - LLM integrations (OpenAI, Anthropic, Gemini) - Multi-agent workflows - AI automation platforms - RAG and knowledge systems - AI infrastructure and backend architecture Financial Infrastructure - Payment platforms - Ledger systems - Stripe, ACH, Plaid and financial integrations - Risk engines - Reconciliation systems - Trading infrastructure - Market intelligence platforms Real-Time Systems - High-volume event processing - WebSocket infrastructure - Streaming architectures - Distributed systems - Low-latency APIs - Event-driven microservices - Kafka, Redis, RabbitMQ and SQS Cloud & Platform Engineering - AWS and GCP - Kubernetes & Docker - Terraform & CI/CD - PostgreSQL, ClickHouse, TimescaleDB, Redis - Observability, monitoring, and production hardening Recent Projects CoinQuant.ai AI-powered quantitative trading platform allowing traders to create trading strategies through natural language, perform tick-level backtesting, and analyze real market data using institutional data providers including Kaiko, Financial Modeling Prep, and CoinGecko. Responsibilities included: - AI architecture - Backend systems - Financial data infrastructure - Strategy engine - Production platform design DeepVue Technical Lead responsible for the migration of a large real-time market intelligence platform from Node.js to Go. Highlights: - SEC financial data ingestion - XBRL and fundamental data processing - High-frequency market data - Formula and screening engine - ClickHouse architecture - Performance optimization - Real-time analytics MoonShot MAGAX Blockchain infrastructure including: - Smart contracts - Token issuance - Vesting - Claims - Backend settlement services - Production AWS infrastructure SoLo Funds Financial platform supporting: - Stripe payments - Subscription infrastructure - Risk systems - Event-driven financial workflows - Production backend architecture Where I Add the Most Value Companies typically bring me in to: - Design scalable platform architecture - Build AI-native products - Rescue struggling engineering projects - Review AI-generated code and improve engineering quality - Lead engineering teams - Design financial infrastructure - Build real-time trading and market data systems - Scale SaaS platforms from MVP to production - Modernize legacy systems - Reduce technical debt without slowing delivery Selected Results - Scaled backend platforms from 10,000 to over 1 million daily transactions - Reduced AWS infrastructure costs by approximately 40% (~$15,000/month) - Migrated £2.4M in active subscriptions with zero downtime - Built highly concurrent Go services capable of processing thousands of parallel workloads - Designed systems targeting 99.99% availability - Led migration of production systems from Node.js to Go - Built AI-powered engineering agents for automated issue investigation, root-cause analysis, ticket generation, and validated code fixes How I Work I believe great engineering starts with good architecture. Every engagement begins with understanding the business problem, identifying technical risks early, and designing systems that remain maintainable years after the first release. I work closely with founders, product teams, and engineering organizations to balance delivery speed with long-term scalability. Whether I'm joining as a Founding Engineer, Fractional CTO, Technical Lead, or Senior Backend Engineer, my objective is always the same: Build the right foundation so the business can scale without constantly rebuilding its technology.

I am a highly-skilled Python developer with more than 10 years of proven experience with Python and 8+ years of working with web development. I have built many web and mobile application backends of various complexity levels. Likewise, I have worked with individual entrepreneurs and with organizations in distributed teams of 25 people from all over the world. I have experience building SaaS and Enterprise projects in different niches. Like: ad-tech, healthcare, fintech and real estate. I often use these libraries during development: - Python: Django, Django Rest Framework, FastAPI, Flask, Pyramid, Asyncio, Aiottp, Tornado, Sqlalchemy, Graphene, Pydantic, Uwsgi, Django ORM, Bottle, Celery, Airflow, Dramatiq, Django channels, Sanic, Twisted. - Server-side: MySQL, PostgreSQL, MongoDB, Redis, Kafka, RabbitMQ, ELK, ElasticSearch, AWS, AWS Lambda, AWS S3, Azure, GCP, REST API, GraphQL, Microservices, Docker, Docker compose, Kubernetes, AWS EC2, WebSockets, Nginx, SSH, Third-party API, PubSub, Debug, Facebook API, Google API, Twitter API, Outlook API, Vagrant, Nginx. - DevOps: AWS, Azure, GCP, Kubernetes, Docker, Docker compose, Prometheus, Grafana, Linux, UNIX, Jenkins, GitLab CI, Github Actions, Bitbucket pipelines, Terraform, Ansible, Bash, CI/CD, Load Balancing, Nginx, Apache. - BigData: Apache Spark, Apache Druid, Cassandra, DynamoDB, Clickhouse - I’m also proficient in JavaScript/NodeJS, Vue, Angular, and React. On Upwork, I hope to find challenging tasks to deepen and expand my server-side development skills, particularly Python. Also, I’m into DevOps engineering and am open to collaboration.

Welcome to my profile 🤟 I'm a Full-Stack Developer with 10 years of experience. I’ve worked on e-commerce projects, CRM systems, and social networks, using various frameworks to create projects from scratch or update and fix existing ones. I can create multiple types of projects, ranging from landing pages to ERPs, social networks, and more. 💻 Technical Skills: ➡️ Programming Languages & Technologies ▪ PHP ▪ JavaScript ▪ Node.js ▪ SQL ▪ C# ▪ Golang ➡️ Frameworks & Libraries ▪ Laravel ▪ CodeIgniter ▪ Bootstrap ▪ Tailwind CCS ▪ Angular 2+ ▪ React.js ▪ Vue.js ▪ Symfony ▪ Zend 3 ▪ Redis ➡️ RDBMS ▪ MS SQL Server ▪ SQLLite ▪ MySQL ▪ PostgreSQL ▪ Clickhouse NoSQL ▪ MongoDB ▪ Elasticsearch ➡️ Virtualization Tools ▪ Vagrant ▪ Docker ➡️ Methodologies ▪ Agile, Scrum, XP ▪ Pair Programming ▪ Test Driven, Feature Driven, Behavior Driven Development ▪ Waterfall ➡️ Application & Web Servers ▪ Apache ▪ Nginx Cloud Providers ▪ AWS ▪ Azure ➡️ Development Tools ▪ IntelliJ IDEA ▪ Visual Studio + ReSharper ▪ Rider ➡️ Testing Tools ▪ Postman ▪ SoapUI ➡️ Operating Systems ▪ Microsoft Windows ▪ SUSE Linux ▪ macOS I'm available to commit 40 hours per week on an ongoing basis. I can work independently and as part of a team. We can jump on a call to talk more and see if we're a good fit 🤝

Marktine Technology — Cloud Data Engineering & AI Specialists I’m Alok Sharma, CEO of Marktine Technology. We are a global IT consulting and development firm with a proven track record in data engineering, data science, cloud migrations, and DevOps automation. Our expertise spans Google Cloud Platform (GCP), Amazon Web Services (AWS), Microsoft Azure, and hybrid architectures — helping clients build scalable, secure, and cost-optimized data platforms. 🔑 Core Competencies Data Engineering End-to-end ETL/ELT pipeline design (batch + streaming) using Apache Beam, Spark, Dataflow, and Airflow. Large-scale data migrations (ELK → ClickHouse, ELK → BigQuery, SQL Server → Cloud data warehouses). SCD Type 2 implementation for dimensional modeling and historical data tracking. Data validation & recovery pipelines — checksum validation, dead-letter queues, reconciliation reports. Performance tuning — optimized Spark code, partitioning, clustering, and materialized views. Data Science & Analytics Predictive & prescriptive analytics on cloud platforms (BigQuery ML, Databricks ML, SageMaker). Marketing attribution modeling & Customer Data Platform (CDP) analytics. Healthcare & Airline analytics — claims processing KPIs, patient metrics, flight/ops dashboards. Graph analytics — Neo4j + GKE for supply chain & relationship insights. Cloud Platforms (GCP • AWS • Azure) GCP: BigQuery, Pub/Sub, Dataflow, Cloud Composer, GKE, Cloud Functions, Cloud Operations. AWS: EMR, Glue, Redshift, MSK/Kinesis, S3, EC2, Lambda, Step Functions. Azure: Databricks, Synapse Analytics, Data Factory (ADF), Data Lake, Azure ML. Hybrid multi-cloud migrations (on-prem → GCP/AWS/Azure). DevOps & Automation CI/CD pipelines using Jenkins, GitHub Actions, GitLab, YAML scripts. Infrastructure as Code (IaC): Terraform, CloudFormation, ARM templates. Docker & Kubernetes orchestration for scalable deployments. Automated monitoring & alerting (CloudWatch, Cloud Operations, Grafana). 🛠️ Technical Skills Big Data & Cloud: ClickHouse, BigQuery, Databricks, Synapse, Redshift, Hadoop, Spark (PySpark/Scala), Hive, Kafka, Pub/Sub, Kinesis Programming: Python, PySpark, Scala, SQL Schedulers & Orchestration: Airflow, Cloud Composer, Oozie, Autosys DevOps Tools: Jenkins, GitHub Actions, GitLab, Docker, Kubernetes, Terraform, Maven, Gradle, SBT Databases: MongoDB, Elasticsearch, MySQL, Oracle, Teradata Monitoring & Validation: CloudWatch, GCP Ops Suite, Prometheus/Grafana Others: JIRA, Git, IntelliJ, Eclipse 🏆 Certifications & Awards DP-203 — Azure Data Engineering (Microsoft Certified) AZ-900 — Azure Fundamentals 📂 Representative Projects ELK → BigQuery Migration (Export Genius) Migrated 20M+ records to GCP using Dataflow + Pub/Sub with recovery pipelines. Orchestrated with Airflow DAGs, validation via BigQuery checks. Delivered a serverless analytics platform with cost optimization. ELK → ClickHouse Migration (AWS Native) Migrated 6.13 billion records using Spark on EMR + ClickHouse on EC2. Built real-time streaming ingestion via Kinesis & Lambda. Achieved 100x query performance improvement vs legacy ELK. Azure Data Engineering for Healthcare Client Built ETL pipelines on ADF + Databricks for claims processing metrics. Implemented SCD Type 2 dimensional modeling for patient history tracking. Delivered interactive Power BI dashboards for medical insights. 🌍 Industry Expertise Marketing: Attribution modeling, CDP data pipelines, campaign performance dashboards. Healthcare: Claims metrics, patient analytics, compliance reporting. Airlines: Operational metrics, passenger insights, schedule optimization. E-Commerce & Retail: Data lakes, recommendation engines, customer churn models. 💡 Why Clients Choose Marktine ✔ Proven at scale — from demo migrations (20M) to enterprise datasets (6B+) ✔ Multi-cloud expertise — AWS, GCP, Azure certified engineers ✔ Transparent delivery — daily logs, MoMs, Upwork timesheets ✔ Cost-efficient architecture — optimized queries, cloud cost monitoring ✔ Flexible models — hourly, fixed, or retainer with EU/US overlap If you’re looking for senior data engineers, data scientists, or cloud experts (GCP, AWS, Azure) to migrate, optimize, or scale your data platform — Marktine Technology can help. Best regards, Alok Sharma CEO, Marktine Technology

With over two decades of experience encompassing DevOps engineering and data engineering, I specialize in architecting robust infrastructure and optimizing data workflows to drive organizational success. My career highlights include designing and implementing CI/CD pipelines, managing diverse cloud environments, and executing complex data migration and ETL processes with a focus on scalability and performance. 𝙆𝙚𝙮 𝙎𝙠𝙞𝙡𝙡𝙨: 𝗖𝗹𝗼𝘂𝗱 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺𝘀: AWS, Azure, GCP, Oracle Cloud, Cloudflare, Hetzner, DigitalOcean 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗮𝘀 𝗖𝗼𝗱𝗲: Terraform, CloudFormation, Ansible 𝗖𝗜/𝗖𝗗: Jenkins, GitLab CI/CD, CircleCI 𝗖𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿 𝗢𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻: Kubernetes, Docker Swarm, ECS 𝗠𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴 𝗮𝗻𝗱 𝗔𝗹𝗲𝗿𝘁𝗶𝗻𝗴: Prometheus, Grafana, ELK Stack, Nagios 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗮𝗻𝗱 𝗖𝗼𝗺𝗽𝗹𝗶𝗮𝗻𝗰𝗲: TLS/SSL, OAuth, PCI DSS, GDPR 𝗡𝗲𝘁𝘄𝗼𝗿𝗸𝗶𝗻𝗴: OpenVPN, IPsec, Cisco ASA 𝗩𝗶𝗿𝘁𝘂𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻: Proxmox, VMware, VirtualBox 𝗪𝗲𝗯 𝗦𝗲𝗿𝘃𝗲𝗿𝘀: Nginx, HAProxy, Apache HTTP Server 𝗗𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗲𝗱 𝗦𝘁𝗼𝗿𝗮𝗴𝗲: Ceph, GlusterFS, Amazon EFS 𝗖𝗼𝗺𝗺𝘂𝗻𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗣𝗿𝗼𝘁𝗼𝗰𝗼𝗹𝘀: WebSocket, MQTT, AMQP 𝗗𝗮𝘁𝗮𝗯𝗮𝘀𝗲 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁: PostgreSQL, MySQL, Oracle, MongoDB, Cassandra 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲𝘀: SQL, Python, Java 𝗕𝗶𝗴 𝗗𝗮𝘁𝗮 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝗶𝗲𝘀: Hadoop, Spark, Kafka 𝗕𝗜 & 𝗗𝗮𝘁𝗮 𝗪𝗮𝗿𝗲𝗵𝗼𝘂𝘀𝗶𝗻𝗴: Azure Data Lake, Power BI, ClickHouse 𝗗𝗮𝘁𝗮 𝗚𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲: Implementing governance frameworks for data quality and compliance 𝙋𝙧𝙤𝙟𝙚𝙘𝙩 𝙃𝙞𝙜𝙝𝙡𝙞𝙜𝙝𝙩𝙨: 𝗪𝗘𝗣𝗔 𝗣𝗿𝗼𝗷𝗲𝗰𝘁: Orchestrated Azure cloud infrastructure setup, implemented robust data pipelines with Kibana, Flink, Kafka, and Power BI. Managed data aggregation from 13+ factory locations, enabling centralized processing and analysis. 𝗥𝗚𝗧𝗡 𝗣𝗿𝗼𝗷𝗲𝗰𝘁: Established comprehensive monitoring services, conducted infrastructure maintenance, and managed server upgrades across multiple environments. Utilized Prometheus, Grafana, MySQL, and Proxmox to optimize system performance and ensure high availability. 𝗗𝗶𝗴𝗶𝘁𝗮𝗹 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻 𝗜𝗻𝗶𝘁𝗶𝗮𝘁𝗶𝘃𝗲𝘀: Led initiatives integrating DevOps and data engineering principles to streamline deployment processes and enhance data-driven decision-making capabilities. Implemented advanced analytics solutions and data lakes for optimized data processing and integration. 𝙒𝙤𝙧𝙠 𝘼𝙥𝙥𝙧𝙤𝙖𝙘𝙝: Dedicated to delivering high-quality solutions aligned with client objectives, I excel in collaborative environments where I leverage my expertise to innovate and optimize infrastructure and data workflows. My proactive approach and commitment to continuous learning ensure I stay ahead in evolving technologies. 𝙇𝙚𝙩'𝙨 𝘾𝙤𝙣𝙣𝙚𝙘𝙩: If you're looking for a seasoned professional who can optimize your infrastructure, streamline deployment and data processes, and ensure scalability and security across your projects, I'm eager to discuss how I can contribute to your organization’s success.

🥇 𝗧𝗼𝗽 𝟭% 𝗼𝗻 𝗨𝗽𝘄𝗼𝗿𝗸 | 💰 𝗖𝘂𝘁 𝗖𝗹𝗼𝘂𝗱 𝗖𝗼𝘀𝘁𝘀 𝟮𝘅–𝟱𝘅 | 📈 𝟮𝟮𝟬+ 𝗣𝗿𝗼𝗷𝗲𝗰𝘁𝘀 𝗗𝗲𝗹𝗶𝘃𝗲𝗿𝗲𝗱 | ⚡ 𝟵𝟵.𝟵𝟵% 𝗨𝗽𝘁𝗶𝗺𝗲 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲𝘀 | 🚀 𝟭𝟬𝟬𝟬+ 𝗩𝗠𝘀 | 𝗣𝗕-𝘀𝗰𝗮𝗹𝗲 𝗰𝗹𝘂𝘀𝘁𝗲𝗿𝘀 | 🧠 𝟮𝟬+ 𝗬𝗲𝗮𝗿𝘀 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 | 🎯 𝟲𝗸+ 𝗨𝗽𝘄𝗼𝗿𝗸 𝗛𝗼𝘂𝗿𝘀 | ❌ 𝗡𝗲𝘃𝗲𝗿 𝗢𝘂𝘁𝘀𝗼𝘂𝗿𝗰𝗲𝗱 | 📩 𝗙𝗮𝘀𝘁 𝗮𝘂𝗱𝗶𝘁 𝗶𝗻 𝟮𝟰𝗵 I help companies cut infrastructure costs 2x by migrating from expensive cloud and SaaS solutions to efficient private cloud environments built on Proxmox and Ceph. Whether you're paying too much for cloud, struggling with scaling, or dealing with unstable infrastructure - I design and implement systems that are faster, cheaper, and easier to manage. I work with high-load production environments: clusters with 1000+ VMs, petabyte-scale storage, and fully automated infrastructure. What I can help you with: • Reduce cloud and infrastructure costs by 50–80% using Proxmox-based private cloud • Migrate from VMware, AWS, or other platforms to cost-efficient infrastructure • Build and optimize Ceph storage (RBD, CephFS, S3) for performance and reliability • Fix performance issues, instability, or scaling problems in existing clusters • Design HA architecture with backup and disaster recovery • Automate infrastructure using Puppet and provisioning pipelines Typical problems I solve: • Infrastructure costs are too high and keep growing • Cloud bills are unpredictable • Ceph clusters are slow, unstable, or constantly rebalancing • Proxmox clusters break, failover doesn’t work, or nodes drop • Backup systems are unreliable or too slow • Monitoring systems (Zabbix) overloaded and ineffective Why clients work with me: • 20+ years in enterprise infrastructure • 200+ real-world projects (not lab setups) • Experience with large-scale production systems • Focus on measurable results: cost reduction, stability, scalability Technologies I use: Proxmox VE, Ceph, Zabbix, Puppet, BGP, VPN, HA clusters, Backup & DR systems If your infrastructure is getting expensive, slow, or hard to manage — I can fix it or rebuild it properly.

CTO and Data/AI Architect with 15+ years building production systems, from early-stage products to Fortune 500 enterprise platforms across the UK, US, and EU. I focus on resilient architecture, clear technical strategy, and AI systems that deliver measurable outcomes in B2B data-rich environments. I've designed and shipped data platforms, agentic RAG systems, multi-agent workflows, AI copilots, and orchestration layers integrating knowledge graphs, semantic layers, and multiple data sources. Domains: SaaS, BI, process intelligence, analytics, fraud detection, supply chain, distributed systems. ① AI & Data RAG end-to-end: chunking, retrieval, reranking, evaluation, monitoring Knowledge graphs: schema design, entity resolution, hybrid KG+RAG retrieval (Neo4j) Multi-agent systems: ReAct, MoE, MoA, hierarchical workflows, tool-using agents Orchestration: MCP, A2A, agent routers, tool registries Observability: latency/cost budgets, guardrails, failure modes, rollout strategy ② Technology Python, SQL, Ruby | Microservices, event-driven, APIs ClickHouse, BigQuery, Redshift, PostgreSQL, Apache Iceberg, Kafka, dbt LangGraph, LangChain, LangSmith, CrewAI, AutoGen, GCP ADK Neo4j, Pinecone, pgvector, Qdrant, FAISS, OpenSearch Docker, Kubernetes, Terraform, Helm, CI/CD Grafana, Prometheus, Looker | AWS, GCP ③ What I Lead CTO-level leadership: strategy, roadmap, delivery governance Data platform architecture: pipelines, modelling, KPIs, governance, cost control AI productisation: prototype to production with evaluation, monitoring, and guardrails Team building: hiring, mentoring, accountability for predictable delivery If you need a CTO-level partner who can architect, build, and lead from strategy to execution, with depth in both AI/Data and engineering reality, I'm the right fit.

✅ Top 1% Expert-Vetted on Upwork | 100% Job Success Score Will fix your broken ETL pipeline Reduce your cloud data costs Build dashboards that actually show profit Improve database performance Orchestrate your data infrastructure Key Skills and Expertise: Data Warehousing SQL Reporting ClickHouse AWS Redshift, Snowflake AWS QuickSight, Interactive BI Dashboards Custom ETL Pipelines Advanced Data Manipulations Python Programming Achievements: 1st Place in Regional Math Olympiad 1st Place in Regional Physics Olympiad SQL DML Specialist Certification Let's collaborate to transform your data into actionable insights and drive your business forward.