Hire the Best MapReduce Specialists

I am a dedicated Data Engineer with a strong foundation in data analytics, specializing in building production-grade data infrastructure, distributed database systems, and scalable ETL pipelines. With 7 years of experience, I help companies: • Transform messy data into automated, reliable, and scalable ETL pipelines for complex financial data that save 100+ hours monthly • Architect distributed database systems: Design multi-tier data architectures for massive-scale record management • Build advanced ETL pipelines with intelligent change detection to process only what's changed, reducing unnecessary processing • Architect cloud-native data solutions and scale data infrastructure across multiple clouds • Automate data workflows to eliminate manual processing and escape Excel Hell • Make massive datasets searchable with Information Retrieval systems • Modernize legacy data systems with cloud & AI solutions • Optimize data infrastructure to reduce costs and improve performance • Design parallel execution frameworks: Implement isolation patterns enabling concurrent pipeline runs without conflicts I have been providing a wide range of services in the realm of data analytics and data engineering such as: • Building ETL pipelines with Prefect orchestration • Distributed database architecture (YugabyteDB, Neo4j, OpenSearch) • Custom dbt materializations and incremental models (SCD-2, temporal tables) • Database optimization and storage compression • Data validation and comprehensive testing frameworks • Per-run schema isolation and parallel pipeline execution • Google Sheets automation and dashboard generation • Excel-to-database migration and formula translation • Multi-source data integration (CSV, Parquet, S3, APIs, databases) • Data Cleaning & Transformation at scale • Operational Efficiency Analysis • Financial metrics calculation systems • Multi-cloud architecture design • Infrastructure as Code (Terraform) • Cloud services integration (AWS, GCP, Azure) • AI/ML service integration (OpenAI, AWS Bedrock) • Automated reporting solutions (Python-Excel integration) • Data Visualization & Dashboarding • Web Scraping & Data Collection While the above services encapsulate my core offerings, I am inherently adaptable and thrive on diving into new challenges and expanding my skill set. Seeking great, enthusiastic projects that will provide me with challenging, interesting work that I can learn from and contribute to. My stack: Data Engineering: ✅ Python ✅ SQL (PostgreSQL, MySQL, SQL Server, YugabyteDB, DuckDB) ✅ Prefect ✅ dbt Cloud & Infrastructure: ✅ AWS (EC2, S3, Glue, RDS, Lambda, EKS, DynamoDB, ECR, Bedrock) ✅ Google Cloud Platform (BigQuery, GKE, Bigtable, Cloud Functions) ✅ Azure (ADF, Synapse, AKS, Cosmos DB, Azure Functions, ACR, Text Analytics) ✅ Terraform ✅ Docker ✅ Kubernetes ✅ Prometheus Data Storages: ✅ RDBMS (PostgreSQL, MySQL, SQL Server, DuckDB) ✅ Object Storage (S3, Wasabi) ✅ Graph Database (Neo4j) ✅ Key-Value Database (Redis, DynamoDB) ✅ Document Database + Search Engine (OpenSearch) ETL & Data Processing: ✅ Pandas ✅ NumPy ✅ Selenium ✅ BeautifulSoup Spreadsheet Automation: ✅ Google Sheets API (gspread) ✅ Excel automation (openpyxl, xlwings) ✅ Automated dashboard generation Data Visualization: ✅ Matplotlib ✅ Seaborn ✅ Plotly ✅ Power BI ✅ Grafana Backend Development: ✅ FastAPI ✅ Flask ✅ RESTful APIs ✅ GraphQL ✅ Redis ✅ Nginx ✅ Gunicorn ✅ WebSocket AI/LLM Integration: ✅ OpenAI API ✅ Anthropic API ✅ Gemini API ✅ AWS Bedrock ✅ Vercel AI SDK ✅ Agno AI

I help businesses build reliable data pipelines, cloud infrastructure, and backend systems that scale. My core work includes Azure Data Factory pipelines, SQL data warehousing, Snowflakes, Terraform-based infrastructure, AWS/Azure deployments, and backend integrations for data-heavy applications. I focus on production-ready systems that are stable, observable, and built for real business use. I have worked on projects such as: • Building Azure-based ETL pipelines and warehouse processes integrating platforms like Shopify, NetSuite, UKG, Air1, and custom systems • Processing large daily data volumes with incremental and full-sync strategies • Designing SQL procedures, reconciliation workflows, and reporting pipelines for operational and executive dashboards • Automating cloud infrastructure and deployments using Terraform, AWS, Jenkins, Docker, and Kubernetes • Improving performance, reliability, and cost-efficiency in backend and AI-driven systems What I can help with: • ETL / ELT pipelines • Azure Data Factory workflows • Azure SQL / PostgreSQL / SQL optimization • Data warehouse design • Backend API integrations • Terraform infrastructure automation • AWS / Azure deployment workflows • Monitoring, logging, and production reliability improvements Why clients work with me: • I understand both data and backend systems, so I can solve integration problems end-to-end • I care about business outcomes, not just writing code • I communicate clearly and keep delivery practical • I build with maintainability and production use in mind If you need help with a data pipeline, warehouse workflow, backend integration, or cloud infrastructure setup, I’d be glad to discuss your project. Certifications: AWS Certified Solutions Architect HashiCorp Terraform Associate

Most data pipelines don’t fail because of code. They fail because they weren't built for scale. With 8+ years of experience engineering data systems at companies like Microsoft and Coreweave, I help businesses move away from "brittle prototypes" to production-grade, scalable infrastructure. I don’t just move data; I build the "Source of Truth" that leadership and AI systems actually trust. 💬What I Solve for You: Productionizing AI Pipelines: Hardening Python prototypes into scalable RAG and LLM infrastructures (AWS/Azure). ➔Infrastructure-as-Code: Building automated, modular ETL/ELT pipelines that don't require daily manual fixes. ➔The "One-Source" Dashboard: Integrating messy data from APIs, SaaS (Shopify, HubSpot), and DBs into clean Snowflake/BigQuery layers. ➔Performance Recovery: Optimizing slow SQL queries and high-cost cloud warehouses to save you thousands in monthly spend. 🛠 Tech Stack: Languages: Python (FastAPI, Pandas, PySpark), SQL Cloud & Warehousing: AWS (Glue, Lambda, S3), Snowflake, BigQuery, Azure Orchestration: Airflow, dbt, GitHub Actions Data Ops: API Integrations, Vector DBs, Data Validation ✅ Why Me? 8+ Years Experience: I’ve seen what breaks at the enterprise level and how to prevent it in your startup. Speed over Perfection: I focus on shipping high-impact systems that drive revenue, not just technical documentation. Transparent Communication: You get regular updates and a partner who challenges requirements to find better solutions. Ready to clean up your data debt? 📩 Message me for a FREE 15-minute technical consultation. Let’s discuss your architecture and see if I’m the right fit for your system.

🚀 I help businesses turn messy, scattered data into clean, automated, decision-ready systems. ⚡ 𝐁𝐢𝐠 𝐃𝐚𝐭𝐚 & 𝐂𝐥𝐨𝐮𝐝 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬 𝐟𝐨𝐫 𝐆𝐥𝐨𝐛𝐚𝐥 𝐂𝐥𝐢𝐞𝐧𝐭𝐬 | 🏆𝟖𝟎+ 𝐏𝐫𝐨𝐣𝐞𝐜𝐭𝐬 𝐃𝐞𝐥𝐢𝐯𝐞𝐫𝐞𝐝 | 📊𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐞𝐝 𝐄𝐓𝐋 & 𝐏𝐨𝐰𝐞𝐫 𝐁𝐈 𝐒𝐩𝐞𝐜𝐢𝐚𝐥𝐢𝐬𝐭 I help startups and growing companies turn scattered, unreliable data into automated, decision-ready systems. From building production-grade ETL pipelines to deploying Power BI dashboards used by executives, I deliver data platforms that are scalable, secure, and cost-efficient. With 𝟒+ years of professional experience and 𝟖𝟎+ successful data projects, I specialize in making data fast, accurate and business-ready. ⚡ 𝐂𝐨𝐫𝐞 𝐄𝐱𝐩𝐞𝐫𝐭𝐢𝐬𝐞 ◼ End-to-End ETL / ELT Pipelines (Airflow, Azure Data Factory, Databricks) ◼ Cloud Data Warehousing & Lakehouse Architecture ◼ Big Data Processing with PySpark & SQL ◼ Database Design, Modeling & Performance Optimization ◼ Data Migration & System Integration (APIs, Legacy Systems, SaaS Tools) ◼ Power BI Dashboards & Analytics Automation 🤝 𝐖𝐡𝐚𝐭 𝐈 𝐂𝐚𝐧 𝐃𝐨 𝐟𝐨𝐫 𝐘𝐨𝐮 ◼Build automated ETL/ELT pipelines (Airflow, ADF, Databricks, AWS Glue) ◼Create cloud data warehouses & lakehouses (Snowflake, Redshift, BigQuery, Synapse) ◼Develop Power BI dashboards & data models used by executives ◼Integrate data from APIs, SaaS tools & legacy systems ◼Improve data quality, performance & reporting speed ◼Migrate on-premise systems to AWS, Azure, or GCP 💬 Smarter data. Faster decisions. Higher ROI. Let’s build pipelines that actually power your growth. 🔑 𝐊𝐞𝐲𝐰𝐨𝐫𝐝𝐬 #DataEngineer #Azure #Databricks #ApacheAirflow #ETLPipelines #BigData #PySpark #SQL #PowerBI #DataMigration #DataIntegration #DataWarehousing #CloudDataEngineering #BusinessIntelligence #DatabaseDesign

🏆 TOP RATED PLUS || Top 1% on Upwork || Expert Vetted || 8+ Years of Experience || 100% Job Success Most data teams are held back by unreliable pipelines, warehouses they cannot trust, and data infrastructure that was never built to scale. That's exactly what I fix. As a Senior Data Engineer, I don't just write SQL and call it a pipeline. I architect end-to-end data systems where reliable ingestion feeds into clean, versioned transformations that power decisions your business can act on. My approach prioritizes fault tolerance, scalability, and observability across both batch processing and real-time analytics workloads. This ensures your data infrastructure is not just functional, but resilient and audit-ready. Whether you need cloud data migration, data platform modernization to a Modern Data Stack (Snowflake/dbt/Airflow, Microsoft Fabric), or streaming analytics infrastructure, I deliver production-grade systems that help technical founders and data teams eliminate pipeline debt, automate complex data workflows, and build scalable infrastructure ready for AI workloads. ------------------------ Where I make the biggest impact: ✅ I lead data migration and data platform modernization projects, replacing brittle ETL and ELT pipelines with a Modern Data Stack built on Snowflake, dbt, Airflow, and Microsoft Fabric. ✅ Every engagement includes Medallion Architecture design, full test coverage, CI/CD for data models, data lineage tracking, and documentation that outlasts the project. ✅ I design data pipelines for both batch processing and real-time analytics, idempotent, schema-drift tolerant, and monitored through data observability frameworks, so failures are caught before they reach your stakeholders. ✅ Warehouse models are built to serve the business: Star Schema, dimensional modeling, dbt projects, analytics engineering best practices, and a metrics layer backed by a data catalog and metadata management. ✅ I architect distributed systems for big data and streaming analytics, including Kafka, Flink, Spark Structured Streaming, exactly-once semantics, dead-letter queues, and end-to-end latency guarantees. ✅ AI data pipelines are engineered to feed LLMs and ML systems with clean, structured, high-quality data, from ingestion through transformation to serving. ✅ I bring governance to data platforms through data mesh, data catalog implementation, metadata management, and data integration across systems. ✅ Data quality and data reliability are enforced end to end, with automated frameworks, SLA monitoring, auditable lineage, and observability that catches bad data before it reaches your stakeholders. ✅ I build AI-ready data infrastructure and lakehouse foundations, Delta Lake, Apache Iceberg, cloud data architecture, and CDC pipelines for near-real-time sync. ✅ Cloud data migration is handled end to end, from legacy warehouse assessment through cutover, with zero data loss and minimal downtime. ------------------------ What I Build With: 🗄️ Warehouses, Lakehouses & Data Lakes: Snowflake, BigQuery, Redshift, Databricks, Microsoft Fabric, Delta Lake, Iceberg ⚙️ Transformation: dbt (Core & Cloud), SQLMesh, Spark, PySpark, Star Schema, Medallion Architecture 🔁 Orchestration: Airflow, Dagster, Prefect, Azure Data Factory, Microsoft Fabric 📨 Streaming: Kafka, Kinesis, Pub/Sub, Flink, Fabric Eventstream 🔗 Ingestion: Fivetran, Airbyte, Matillion, Stitch, Hevo, Meltano, CDC pipelines ☁️ Cloud: AWS, GCP, Azure 🐍 Languages: Python, SQL (Snowflake, BigQuery, T-SQL, PL/pgSQL) 🗃️ Databases: PostgreSQL, MySQL, SQL Server, DynamoDB, MongoDB 📊 BI & Reporting: Looker, Tableau, Power BI, Metabase, Superset, Streamlit ------------------------ 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 ⭐ "Adarsh built our entire data platform from the ground up. Clean architecture, solid dbt models, and Airflow pipelines that have been 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 Adarsh with a Spark pipeline that was costing us a fortune and delivering stale data. He diagnosed the bottlenecks, restructured the job logic, and cut our processing time by 70%. Technically sharp, communicates clearly, and delivers without hand-holding." – Leo, Head of Analytics, HealthTech SaaS ------------------------ 🚀 Let's Build Your Data Foundation 📩 If your data infrastructure needs to be faster, cleaner, and something your team can trust, send a quick message about your project and I'll take it from there.

I help companies turn messy, fragmented data into reliable infrastructure that powers analytics, automation, and AI. With a team of 20+ engineers, I deliver production-grade data systems — not prototypes that break in the real world. What I do: Data Engineering — Build scalable ETL/ELT pipelines, data warehouses, and lakehouses (Snowflake, BigQuery, Databricks, Redshift) AI-Ready Infrastructure — Set up RAG pipelines, vector databases (Pinecone, Weaviate, pgvector), and LLM integrations that connect your data to AI Pipeline Orchestration — Automate workflows with Airflow, dbt, Dagster, and Prefect Analytics & Dashboards — Deliver decision-ready reporting in Power BI, Tableau, and Looker Cloud & DevOps — Architect on AWS, GCP, and Azure with cost efficiency and reliability in mind Tech stack: Python, SQL, Spark, dbt, Airflow, Snowflake, Databricks, LangChain, OpenAI/Anthropic APIs, AWS/GCP/Azure Why work with me: ✅ End-to-end ownership — from data ingestion to AI deployment ✅ Backed by a full engineering team for speed and scale ✅ Clear communication, on-time delivery, and clean documentation ✅ Proven track record across startups and enterprise clients Whether you need a single pipeline fixed or a complete AI-ready data platform built from scratch, I bring the technical depth and reliability to get it done right. Let's talk about your project — send me a message and I'll respond within a few hours.