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Messy data slowing your team down? I build scalable ETL/ELT pipelines and modern cloud architectures on Azure, Databricks, Fabric, and Snowflake that turn raw, chaotic data into clean, analytics-ready systems fast and reliably. I bridge the gap between fragmented data sources and production-grade dashboards, seamlessly adapting to your existing infrastructure rather than forcing an expensive rebuild. What I Can Help You With: Data Warehouse & Lakehouse Architecture: Implementing Medallion design patterns (Bronze → Silver → Gold) using Delta Lake, Microsoft Fabric OneLake, and Snowflake. Scalable ETL/ELT Ingestion: Building automated, metadata-driven pipelines via Azure Data Factory, Fabric Pipelines, Databricks (PySpark/SQL), and dbt. Real-Time Data Streaming: Architecting low-latency workflows using Apache Kafka, Azure Event Hubs, and streaming engines. Database Design & Optimization: Performance tuning, indexing, and data modeling for PostgreSQL, Azure SQL, and cloud warehouses. Proven Project Highlights: Microsoft Fabric Incremental Pipeline: Built a control-table pattern using Get Metadata, Lookup, and ForEach loops to orchestrate zero-duplicate, quarterly ingestion from SharePoint into OneLake via Dataflow Gen2. Azure/Databricks Streaming: Developed a restaurant analytics platform processing 80,000+ events/day, cutting reporting lag from 6 hours to under 3 minutes. Kafka/Snowflake Pipeline: Engineered a real-time stock market data pipeline tracking 120+ tickers with under 8 seconds end-to-end latency. I write clean, documented code your team can maintain long-term and provide transparent daily updates. Message me with your data challenge and I’ll walk you through exactly how to solve it.

🏆 Top Rated Plus 🌟 100% Job Success 🤝 Satisfied Clients ⏱ Quick Turnaround 📞 Clear Communication Why work with me? Proven Experience: 💎 Backed by 15+ years of delivering results through scalable, cost-efficient data solutions. Technical Expertise: 💎 AI-Data Architecture: I deliver real-world-ready data through automated, reliable pipelines. The new AI era requires a new data platform. 💎 Conversational Analytics & AI Agents: Enable users to chat with their data through AI-driven interfaces. Google Conversational Analytics API and Gemini Enterprise 💎 Data Visualization: Skilled in Looker, Looker Studio, Power BI, Tableau, Superset, and others. 💎 Data Web Portals: Skilled in developing custom embeddable solutions and full web platforms under your own brand and domain. 💎 Database Management: Expertise in SQL (BigQuery, SQL Server, Oracle, MySQL, PostgreSQL, Snowflake) and NoSQL systems. 💎 ETL: Experience with both streaming and batch pipelines using Airflow, Apache Beam, Kafka, Debezium, Pub/Sub, and others. 💎 Data Modeling: Proficient with dbt, Dataform, and PySpark. 💎 Version Control: Comfortable with Git-based tools (GitHub, Bitbucket, GitLab, Azure DevOps). 💎 Cloud Platforms: Certified and experienced in GCP, AWS, and Azure. 💎 Unstructured Data: JSON, XML, Excel, Google Sheets. 💎 GA4 Data: Google Analytics 4 for advanced analysis. Soft Skills & Work Ethic: 💎 Versatile & Adaptive: Quick to learn new tools, roles, and business domains. 💎 Value-Driven: Focused on delivering high-impact outcomes with cost-efficiency. 💎 Detail-Oriented: Committed to precision and quality in every task. 💎 Reliable & Time-Conscious: Consistent delivery of high-quality work on time. 💎 Leadership: Capable of guiding teams and leading initiatives when needed. 💎 Analytical: Skilled at breaking down complex problems and finding effective solutions. 💎 Collaborative: Strong team player, effective in multidisciplinary environments. Scalable Technical Capacity: I’m supported by a network of 15+ specialists, including Solution and Data Architects, Developers, Designers, Process Specialists, DevOps Engineers, Machine Learning Engineers, Data Scientists, Data Analysts, and more. We work collaboratively to ensure your project receives the strongest possible technical support, from strategy to execution. How I approach projects: - Kick-off meeting to review requirements and deliverables - Action plan development using a project management tool - Weekly demo meetings to showcase progress - Detailed time and task tracking - Continuous feedback loop to ensure alignment and improvement - Complete documentation of the solution

A working demo and a system that survives production are two very different things. I build the second kind. Over a decade of backend engineering and 70+ completed projects on Upwork. I run Datum Brain, a software and AI engineering company, so you get one senior engineer accountable end to end, with a team behind him when the work needs it. We ship Go microservices, data pipelines, and LLM systems for FinTech, SaaS, EdTech, and AdTech clients. Recent work: 🛡 Real-time ad fraud detection (TrueAudience) High-concurrency Go backend that scores ad traffic to catch bots before advertisers pay. 80M+ events, under 20ms decisions. Go, TimescaleDB, real-time pipelines. 🏦 Go microservices for an EMI and payments platform (Zolvat) Ledger logic, payment flows, and service orchestration for an installment payments platform. Go, microservices, PostgreSQL. 🎥 WebRTC proctoring infrastructure (Meazure / Examity) Real-time media and session orchestration for thousands of concurrent exam sessions at one of the largest US proctoring providers. Go, WebRTC, LiveKit, NATS. 📊 Big data pipeline optimization (Nike) Cut processing time and compute cost on large PySpark workloads. PySpark, AWS. 📄 Document intelligence platform (Centrum AI) OCR and RAG pipeline that turns unstructured documents into structured, queryable data with human review. Python, FastAPI, LangChain, RAG. What I work with: Backend: Go, Python, FastAPI, gRPC, REST, PostgreSQL, TimescaleDB, Redis, NATS, Kafka Data: PySpark, ETL pipelines, data quality frameworks, AWS, GCP Real-time: WebRTC, LiveKit, event streaming, high-concurrency systems AI and LLM: LangChain, LangGraph, RAG, multi-agent systems, OpenAI, Claude, evals Infra: Docker, Kubernetes, CI/CD, nginx How I work: I scope before I quote, so you know what you are getting and when. I flag risks early instead of at the deadline. Production-ready means tested, documented, monitored, and handed over properly. Good fit if you need something that runs in production and not a proof of concept, you want one senior engineer accountable end to end, and you value clear communication and honest scoping. Not a fit if you are shopping purely on hourly rate, or the spec changes daily and nobody owns decisions. If your backend needs to handle real load, or your data or AI work needs to go from demo to product, send me a message.

I'm a Senior Data Engineer with 8+ years of strong technical expertise in building reliable and scalable data infrastructure, from data ingestion to transformation to warehousing, streaming, and data analytics, specializing in dbt, Snowflake, Airflow, Databricks (and more) across AWS, Azure, and GCP, with robust ELT and ETL pipelines. If your data pipelines are brittle, your data warehouse is slow, or your data was never built to scale, that is exactly what I fix, with fault tolerance, observability, and audit-ready quality engineered in from day one. I cover the full data engineering lifecycle: batch and real-time data pipelines, Modern Data Stack builds, lakehouse architecture, cloud and warehouse data migration, governance, and the data foundations that feed modern systems. 🎯 Core Expertise: ✅ Data Pipelines & Orchestration: End-to-end batch and real-time pipelines with Apache Airflow, Dagster, Prefect, AWS Step Functions, and Azure Data Factory. Idempotent, schema-drift tolerant, and monitored so failures surface before they reach your stakeholders. ✅ Cloud Warehousing & Lakehouse: Snowflake, BigQuery, Amazon Redshift, Databricks, and Microsoft Fabric, with Delta Lake and Apache Iceberg lakehouse foundations governed through the Glue Data Catalog and Lake Formation, with Athena and Redshift Spectrum for serverless queries, Medallion Architecture, partitioning, and performance tuning. ✅ Data Transformation & Modeling: dbt (Core and Cloud), SQLMesh, Spark and PySpark on EMR and AWS Glue, Star Schema and dimensional modeling, analytics engineering best practices, full test coverage, and CI/CD for data models. ✅ Streaming & Real-Time Analytics: Distributed streaming with Apache Kafka, Flink, Spark Structured Streaming, Kinesis, and Pub/Sub, including exactly-once semantics, dead-letter queues, CDC, and end-to-end latency guarantees. ✅ Data Ingestion & Integration: Fivetran, Airbyte, Matillion, Stitch, Hevo, Meltano, and custom CDC pipelines for near-real-time sync across structured, semi-structured, and unstructured sources. ✅ Data Quality, Governance & Observability: Automated data quality frameworks, SLA monitoring, auditable lineage, data catalog and metadata management, and observability that catches bad data early. ✅ Cloud Migration & Modernization: Zero-downtime migration handled end to end, from legacy warehouse assessment through cutover, with zero data loss and minimal downtime, replacing brittle ETL and ELT with a clean Modern Data Stack. ✅ AI-Ready Data Infrastructure: Pipelines engineered to feed LLMs and ML systems with clean, structured, high-quality data, from ingestion through transformation to serving. ------------------------------------------------------ ⚙️Tech Stack: ⚡ Warehouses & Lakehouse: Snowflake | BigQuery | Redshift | Databricks | Microsoft Fabric | Athena | Delta Lake | Iceberg ⚡ Transformation: dbt | SQLMesh | Spark | PySpark | AWS Glue | EMR | Star Schema | Medallion Architecture ⚡ Orchestration: Airflow (GCP Cloud Composer and AWS MWAA) | Dagster | Prefect | Azure Data Factory | Step Functions ⚡ Streaming: Kafka | Flink | Kinesis | Pub/Sub | Spark Structured Streaming | ClickHouse ⚡ Ingestion: Fivetran | Airbyte | Matillion | Stitch | Hevo | Meltano | CDC ⚡ Governance & Catalog: Glue Data Catalog | Lake Formation | Unity Catalog | Microsoft Purview | Dataplex ⚡ Cloud: AWS | GCP | Azure ⚡ Languages: Python | SQL (Snowflake, BigQuery, T-SQL, PL/pgSQL) | FastAPI ⚡ Databases: PostgreSQL | MySQL | SQL Server | DynamoDB | MongoDB ⚡ BI & Reporting: Looker | Tableau | Power BI | GA4 | Metabase | Superset | Streamlit | Grafana ------------------------------------------------------ ⭐ What Clients Say: 🏅 "Adarsh rebuilt our analytics pipeline on Snowflake, Airflow, and dbt, giving us reliable, version-ready data. Reporting accuracy improved overnight, and we can finally trust the numbers." – Anita, Head of Product, FinTech SaaS 🏅 "He designed a zero-downtime migration to a modern data warehouse that cut query latency by more than half while keeping our SLAs intact." – Daniel, VP of Data, AdTech Firm 🏅 "Clean architecture, solid dbt models, and Airflow pipelines running without issues for months. He brought a level of engineering discipline we hadn't seen from a data consultant before." – Mark, Director of Data Engineering, E-commerce Startup 🏅 "We came to him with a Spark pipeline costing us a fortune and delivering stale data. He restructured the workflow logic and cut processing time by 70%." – Leo, Head of Analytics, HealthTech SaaS ------------------------------------------------------ 🏆 TOP RATED PLUS | EXPERT-VETTED | Top 1% on Upwork | 8+ Years Experience | 100% Job Success 🚀 Ready to build a scalable, production-ready data infrastructure to turn your raw data into reliable, actionable business insights? Click the 'Invite to Job' button on the top right, and let's discuss your data pipeline!

I am a tech-agnostic data engineer who enjoys solving complex data problems, finding patterns in messy datasets, and making sure the work actually supports the business. My focus is always on clean architecture, performance, and making data useful - not just moving it around.Here is what I have worked with: - Programming & Scripting: Python (Flask, FastAPI, Django, Selenium, PySpark), SQL - Data Engineering & Integration: Talend, Mage.ai, Apache Airflow, Airbyte, Databricks, Kafka, Debezium - Databases & Data Warehousing: Data Modeling, PostgreSQL, MySQL, Snowflake, Greenplum, MongoDB, Firebase, ClickHouse - Cloud & DevOps: AWS (Lambda, API Gateway, S3, RDS, SQS and more), Docker, Kubernetes, Azure DevOps, Terraform, CloudFormation - Security & Compliance: Secure and compliant pipeline design (HIPAA, GDPR, SOC 2), data governance, privacy-first architectures - Testing & Automation: Postman, Cypress.io, Swagger, Automated Data Workflows - Data Visualization: Power BI, Metabase, Google Data Studio, Grafana - Collaboration & Leadership: Cross-functional team mentoring, process optimization, data-driven decision-making

✅ Top Rated Plus | 100% JSS | 4x Certified (AWS SA Pro, GCP Pro Architect, Snowflake) | BITS Pilani MTech Data Science | Full Stack Developer & Data Engineer | React, Python, Node.js, Spark | $20K+ earned | 1,845+ hours I build full-stack web applications and data engineering systems that go to production, not to demo day. SaaS MVPs, Spark-based ETL pipelines, cloud architecture on AWS and GCP, I handle both the application layer and the data infrastructure behind it. 🔹 Full-Stack SaaS & Web Application Development React, Next.js, Node.js, and Python backends for SaaS platforms, dashboards, internal tools, and customer-facing apps. MVP to production on AWS/GCP with CI/CD, automated testing, and monitoring from day one. 19 Upwork contracts delivered with structured milestones. 🔹 Data Engineering & ETL Pipeline Architecture End-to-end data pipeline design with Apache Spark, PySpark, Scala, Snowflake, and Airflow. Batch and streaming ETL processing millions of records per run. Data lake architecture, warehouse modeling, analytics-ready output layers. 8+ years building production Spark + Cassandra systems at enterprise scale. 🔹 Cloud Architecture & Infrastructure (AWS + GCP) 4 cloud architecture projects on Upwork, all rated 5.0. $2,300 CloudStack design. AWS architecture advisory. EC2, Lambda, S3, RDS, EMR, Redshift on AWS. BigQuery, Dataflow, Cloud Functions on GCP. Terraform for IaC, Docker and Kubernetes for orchestration, zero-downtime deployments. 🔹 API Development & Backend Systems REST API and GraphQL backends with Node.js, NestJS, FastAPI, and Django. Microservices, Redis caching, WebSocket integrations, Stripe payment APIs, OAuth/JWT authentication. Backend services handling concurrent users at production scale. 🔹 Database Design & Data Modeling PostgreSQL, MongoDB, MySQL, Cassandra, DynamoDB, Redis. Schema design, query tuning, indexing, partitioning. Star and snowflake schemas, slowly changing dimensions, SQL optimization for analytics. Architecture decisions balancing performance, throughput, and cost. 🔹 AI Integration & Intelligent Applications OpenAI API, Hugging Face, NLP pipelines, chatbot systems, text extraction and summarization. Delivered NLP processing on Upwork. AI-powered features built into SaaS products as production features, not standalone experiments. 🔹 Real-Time Processing & Event-Driven Systems Kafka for event-driven architectures, change data capture, WebSocket dashboards, streaming pipelines for near-real-time analytics. Application events connected to data warehouse layers. 🔹 Frontend Performance & TypeScript Engineering React and Next.js with SSR/SSG for SEO-friendly rendering. TypeScript full stack. Core Web Vitals optimization, Tailwind CSS, responsive design. Fast-loading frontends that rank and convert. 🔹 DevOps, CI/CD & Production Systems Docker, Kubernetes, Terraform, GitHub Actions, GitLab CI. Serverless with AWS Lambda and GCP Cloud Functions. Monitoring, logging, alerting for production. Zero-downtime deployment strategies. 🔹 Technical Consulting & Architecture Advisory TypeScript and AWS Lambda tutor on Upwork, rated 5.0 over 13 hours. Cloud migration advisory, system design review, code audits, performance optimization, engineering mentorship. 📊 AWS Solutions Architect Professional + Associate (Dec 2026) | GCP Pro Cloud Architect (Jul 2026) | Snowflake Core (Jan 2026) 📊 MTech Data Science, BITS Pilani, ranked top 5 engineering institutions in India 📊 19 contracts, 100% JSS, Top Rated Plus, 1,845+ hours tracked, $20K+ earned 📊 "Jay's expertise brought the architecture design to life in ways I hadn't imagined" (5.0 rated) 📊 8+ years: React, Node.js, Python, Java, Scala across SaaS, healthcare, fintech, enterprise → Day 1: Requirements call + architecture proposal with tech stack rationale → Week 1: Sprint development, daily Loom/Slack updates, working code shipped → Ongoing: Weekly demos, priority reviews, transparent tracking, full documentation → Delivery: Documented code, CI/CD configured, deployment guide, 2-week post-launch support Full Stack: React, Next.js, Node.js, NestJS, Express, TypeScript, JavaScript, Python, FastAPI, Django Data: Apache Spark, PySpark, Scala, Snowflake, Airflow, Kafka, ETL, dbt, SQL, BigQuery Cloud: AWS (Lambda, EC2, S3, RDS, EMR, Redshift), GCP (BigQuery, Dataflow), Docker, Kubernetes, Terraform DB: PostgreSQL, MongoDB, MySQL, Redis, Cassandra, DynamoDB, Supabase AI: OpenAI API, Hugging Face, NLP, LLM Integration, TensorFlow, PyTorch 💬 Message me with your project scope or data challenge. I respond within 4 hours with a free assessment and can start within 48 hours.