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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, 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, Medallion Architecture, partitioning, and performance tuning. ✅ Data Transformation & Modeling: dbt (Core and Cloud), SQLMesh, Spark and PySpark, 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 | Delta Lake | Iceberg ⚡ Transformation: dbt | SQLMesh | Spark | PySpark | Star Schema | Medallion Architecture ⚡ Orchestration: Airflow (GCP Cloud Composer and AWS MWAA) | Dagster | Prefect | Azure Data Factory ⚡ Streaming: Kafka | Flink | Kinesis | Pub/Sub | Spark Structured Streaming | ClickHouse ⚡ Ingestion: Fivetran | Airbyte | Matillion | Stitch | Hevo | Meltano | CDC ⚡ 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!

✅ 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.

I help businesses build scalable data platforms, AI-driven systems, and high-performance analytics using Databricks, PySpark, and Power BI. If your pipelines are slow, dashboards are lagging, or cloud costs are rising, I can optimize and redesign your system for speed, scalability, and cost efficiency. What I Can Help You With: 1. Build end-to-end data pipelines across Azure, AWS, and GCP using Databricks, PySpark, and modern Lakehouse architecture 2. Develop AI-enabled data systems including anomaly detection, predictive pipelines, and intelligent automation 3. Design and optimize Power BI and Tableau dashboards with fast, scalable data models 4. Implement real-time and batch processing pipelines using Spark and streaming frameworks 5. Reduce cloud costs through FinOps strategies, performance tuning, and architecture optimization 6. Integrate APIs, databases, and event streams into unified analytics platforms 7. Fix slow pipelines, broken workflows, and performance bottlenecks Why Clients Work With Me 1. Architect-level expertise with strong hands-on implementation 2. Experience building multi-tenant, large-scale data platforms (TB–PB scale) 3. Focus on performance, cost optimization, and real business outcomes 4. Clear communication and reliable delivery Certifications & Expertise 1. Azure Solutions Architect Expert 2. Databricks Certified Data Engineer Professional 3. Microsoft Certified: Azure Data Engineer Associate 4. Microsoft Certified: Power BI Data Analyst 5. Azure AI Engineer (AI-102) If you are looking for someone who can combine data engineering, AI, and analytics to build scalable and intelligent data systems, I would be happy to help.

I am a Data Architect with 5+ years’ experience in data engineering in Healthcare, Retail and Banking domains. Worked on multiple data warehousing and reporting projects with open source tools such as Apache Spark, Apache Airflow, Apache Kafka, Apache Superset. I also have experiance in open building open source data warehouses. I am microsoft certified data engineer and Azure administarator. With 5+ years of expirance in Microsoft azure technologies such as Azure Data Factory, Azure Databricks, MS SQL, Azure Synapse etc. I am Microsoft, Databricks and GCP Certified Data Engineer and am currently working as a Data Architect at FulzTech.

I'm a Senior Data Engineer with 4.5+ years of experience building scalable, cloud-native data platforms that turn raw data into reliable, business-ready insights. I've delivered enterprise solutions across banking (NAB), healthcare (Molina), and CPG (PepsiCo), specializing in end-to-end pipeline architecture, data modeling, and cloud migrations. What I bring to your project: 🔹 Cloud Data Engineering – Deep expertise in Azure (Databricks, Data Factory, Synapse) and AWS (EMR, Glue, S3, RedShift), with hands-on migration experience from on-prem and Teradata to cloud. 🔹 Pipeline Architecture & ETL – I design and build robust ingestion frameworks handling batch, incremental, and real-time data (Event Hub, Kafka) across formats like JSON, CSV, Parquet, and fixed-width files. 🔹 Data Modeling & Warehousing – Skilled in dimensional modeling, Data Vault, star/snowflake schemas, and silver/gold layer design. I've modeled 50+ tables across Oracle Fusion, SAP S/4, and healthcare domains. 🔹 Transformation & Orchestration – I translate complex business rules into DBT models, orchestrate workflows with Apache Airflow or AutoSys, and automate CI/CD via Jenkins and Azure DevOps. 🔹 Performance & Governance – I tune PostgreSQL and Spark jobs, implement data quality checks, reconciliation frameworks, and ensure compliance with data governance standards. 🔹 Generative AI & MLOps – Databricks-certified in Generative AI, with experience integrating MLflow for experiment tracking and building LLM-based automation using OpenAI and LangChain. Tech Stack: Python | SQL | Scala | Apache Spark | DBT | PostgreSQL | Snowflake | Airflow | Databricks | Azure | AWS | Git | Jenkins | MLflow | Power BI Certifications: Databricks Certified Data Engineer Professional | Azure Data Engineer (DP-203) | Snowflake SnowPro Core | Fabric Analytics Engineer (DP-600) | Generative AI Engineer Associate Whether you need a production-grade pipeline, a cloud migration, or a well-modeled data warehouse, I deliver clean, documented, and scalable solutions — on time and with clear communication. Let's discuss your project!

I have a 12 years experience In Devops. I'm able build data pipelines on any cloud platform or even on promise. Experienced Python developer (also proficient in Typescript, R, SQL) with a data science background, experienced in building batch and streaming data pipelines, infrastructures, and bringing machine learning models to production. Familiar with common data tech stacks, architecture design, DevOps, and ML (Data Science) including Airflow, Kafka, Hadoop, PySpark, Kubernetes, AWS, Google Cloud Platform. The different services I can provide are the following. -Machine learning / Deep learning algorithms - Database migration (BigQuery, Redshift, Postgres, MySQL, etc). - Datawarouse architecture. - ETL developments (Python, Scala, Spark). - Data pipelines architecture and deployments (airflow, Kubernetes). - Applications containerization (Docker, Kubernetes) - Big data processing using Spark Scala - Building large Scale ETL - Could Management - Distributed platform development - Machine learning - Python Programming - Algorithm Development - Data Conversion (Excel to CSV, PDF to Excel, CSV to Excel, Audio) - Data Mining - CI/CD - Data extraction - ETL Data Transformation - Data Cleansing - OCR (Optical Character Recognition w/ Tesseract) - Linux Server Administration - Anaconda Python / Conda / Miniconda Administration - LXC/LXD Virtualization / Linux Containers - Website & Data Migrations I am highly attentive to detail, organised, efficient, and responsive. Let's get to work! 💪 Since my profile is brand new, I offer my service for low price because I need to improve my reputation.