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Need a data platform that works in production, not just on a whiteboard? I design and build end-to-end data systems that turn fragmented raw data into trusted analytics and AI-ready infrastructure. 10+ years experience. Founder of Vyntics. Delivered consulting solutions for AT&T, Patreon, Jumio & Acko. WHAT YOU GET: Reliable ETL/ELT pipelines (batch + streaming) that keep dashboards accurate and stop 2 AM debugging Cloud data platforms (AWS/GCP) optimized for scale, cost control, and long-term maintainability Production-grade AI/RAG systems: accurate retrieval, eval pipelines, and scalable deployment Legacy-to-cloud migrations with zero-downtime cutovers and built-in validation frameworks PROVEN IMPACT: Migrated enterprise warehouse to BigQuery: 40% lower query costs, zero downtime Built Databricks lakehouse (Delta + Unity Catalog) for governed self-service analytics Designed Snowflake + dbt architecture that cut ELT dev time by 60% Deployed RAG systems on real-world data with measurable accuracy and latency improvements HOW I WORK: Flexible engagement: I can architect your system in a focused 2-week discovery sprint, or lead full end-to-end delivery via my Vyntics team. Always production-first, cost-aware, and documented for your team's long-term success. BEST FIT FOR: Startups scaling infrastructure | Companies migrating legacy systems | Teams adding AI/RAG | Leaders who want clarity before heavy investment Evaluating your data strategy or stuck on architecture decisions? Message me with your challenge. I will reply with 2-3 actionable next steps, no obligation. Arun Mudgal Founder & Principal Consultant, Vyntics

Struggling to unlock value from your data or build scalable, high-performance analytics platforms? I’m 𝑯𝒂𝒔𝒆𝒆𝒃 𝑨𝒔𝒊𝒇,a Senior Data Engineer specializing in Databricks, Snowflake, Big Data Engineering, and scalable ETL/ELT solutions. With expertise in PySpark, Python, SQL, GCP, AWS, Azure, and NLP, I build high-performance data pipelines, cloud data platforms, and real-time analytics solutions. Experienced in data warehousing, cloud integration, machine learning workflows, and performance optimization to transform raw data into actionable business insights. Let’s build reliable, scalable, and data-driven solutions for your business growth. I’ve successfully completed 99+ projects across industries, designing ETL pipelines, MLOps workflows, Delta Lake architectures, and cloud analytics solutions on AWS, Azure, and GCP. ✔️ 𝑯𝒐𝒘 𝑰 𝑯𝒆𝒍𝒑 𝑩𝒖𝒔𝒊𝒏𝒆𝒔𝒔𝒆𝒔 𝑻𝒓𝒂𝒏𝒔𝒇𝒐𝒓𝒎 𝑫𝒂𝒕𝒂 𝒊𝒏𝒕𝒐 𝑰𝒏𝒔𝒊𝒈𝒉𝒕𝒔 ➜ Databricks & Big Data Engineering I specialize in designing enterprise-grade Databricks Lakehouse architectures and Delta Lake solutions. My expertise in Spark and PySpark allows me to build high-performance pipelines for both batch and real-time analytics, ensuring your data infrastructure is robust and scalable. ➜ Machine Learning & MLOps With a focus on machine learning and MLOps, I build and deploy predictive models using tools like MLflow and TensorFlow. I automate end-to-end ML pipelines to enhance efficiency and accuracy, driving impactful insights from your data. ➜ Cloud & Data Platforms I implement secure, scalable cloud solutions on platforms like AWS, Azure, and GCP. My experience includes cloud migration, Kubernetes, Docker, and CI/CD automation, ensuring seamless integration and optimal performance. ➜ ETL & Data Pipelines I develop reliable ETL processes and data pipelines that streamline data integration and transformation. My work with streaming analytics using Kafka and Spark ensures real-time data processing and actionable insights. ➜ Data Analyst & Visualization I create actionable dashboards and visualizations using Power BI, Tableau, and Databricks SQL. My focus is on driving KPI reporting and business intelligence to support strategic decision-making. ➜ Snowflake I leverage Snowflake's capabilities to build efficient data warehousing solutions, optimizing data storage and retrieval for enhanced performance and scalability. ➜ Python My proficiency in Python allows me to develop complex data processing scripts and machine learning models, ensuring robust and efficient data handling. ➜ NLP (Natural Language Processing) I apply NLP techniques to extract meaningful insights from unstructured data, enabling advanced text analytics and improved decision-making processes. ➜ GCP (Google Cloud Platform) I utilize GCP's powerful tools to design and deploy scalable cloud solutions, ensuring high availability and performance for your data-driven applications. ➜ Data Warehouses I design and manage data warehouses that provide a centralized repository for your data, facilitating efficient data analysis and reporting. ✔️ 𝑲𝒆𝒚 𝑻𝒐𝒐𝒍𝒔 & 𝑻𝒆𝒄𝒉𝒏𝒐𝒍𝒐𝒈𝒊𝒆𝒔 ▪ Databricks & Big Data: Databricks, Delta Lake, Apache Spark, PySpark, Unity Catalog, Kafka, Hadoop, Real-time Streaming ▪ Machine Learning: MLflow, TensorFlow, PyTorch, scikit-learn, Feature Store, Predictive Analytics, NLP ▪ Cloud Platforms: AWS, Azure, GCP, Kubernetes, Docker, CI/CD ▪ Analytics & BI: Power BI, Tableau, Databricks SQL, KPI Dashboards, Data Strategy ▪ Data Engineering: ETL Pipelines, Data Lakes, Data Warehousing, Data Migration, Performance Optimization ✔️ 𝑾𝒉𝒚 𝑪𝒉𝒐𝒐𝒔𝒆 𝑴𝒆 I combine deep technical expertise with practical business understanding, delivering scalable, cost-efficient, and AI-ready data solutions. My goal is to turn your data into a strategic asset that powers smarter decisions and measurable growth. Let’s collaborate to build your next-generation analytics platform and unlock the full potential of your data. Check my portfolio for architecture samples, dashboards, and case studies. Databricks Engineer, Big Data Consultant, Spark Developer, MLOps Engineer, Data Engineer, AWS Data Specialist, Azure Databricks, GCP Analytics, ETL Developer, Data Analytics, Delta Lake Expert, Machine Learning Engineer, Python, Database Architecture, Data Processing, ETL, Big Data, Database Design, Data Engineering, Data Analytics & Visualization Software, Data Visualization, Deep Learning Modeling, Data Warehousing & ETL Software, Snowflake, Amazon Web Services, ETL Pipeline, Machine Learning, Deep Learning, Data Science, Data Analysis, Cloud Engineering, Artificial Intelligence, Databricks Engineer, Big Data Consultant, Spark Developer, MLOps Engineer, Data Engineer, AWS Data Specialist, Senior Data Engineer specializing in Databricks, Snowflake, Big Data Engineering, and scalable ETL/ELT solutions. With expertise in PySpark, Python, SQL, GCP, AWS, Azure, and NLP

🏆 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 build and migrate enterprise data platforms on 𝐒𝐧𝐨𝐰𝐟𝐥𝐚𝐤𝐞, 𝐃𝐚𝐭𝐚𝐛𝐫𝐢𝐜𝐤𝐬, 𝐀𝐖𝐒, and modern AI infrastructure, turning fragmented data sources into reliable warehouses, intelligent automation systems, and production-ready AI applications that business teams can actually trust. Over the last decade I've architected data infrastructure, analytics platforms, and AI-powered systems for 𝐑𝐞𝐚𝐥 𝐄𝐬𝐭𝐚𝐭𝐞 (𝐘𝐥𝐨𝐩𝐨), 𝐓𝐞𝐥𝐞𝐜𝐨𝐦 (𝐎𝐨𝐫𝐞𝐝𝐨𝐨 𝐐𝐚𝐭𝐚𝐫), 𝐅𝐢𝐧𝐭𝐞𝐜𝐡 (𝐒𝐢𝐦𝐩𝐥𝐞𝐝𝐂𝐚𝐫𝐝), 𝐇𝐞𝐚𝐥𝐭𝐡𝐜𝐚𝐫𝐞 (𝐌𝐞𝐝𝐂𝐡𝐚𝐫𝐭), and 𝐑𝐞𝐭𝐚𝐢𝐥 (𝐌𝐢𝐥𝐥𝐢𝐨𝐧 𝐃𝐨𝐥𝐥𝐚𝐫 𝐁𝐚𝐛𝐲), integrating 700+ data sources into Snowflake, Redshift, Databricks Lakehouse, and AI-powered ecosystems that support thousands of daily users. → 𝐖𝐡𝐚𝐭 𝐈 𝐃𝐞𝐥𝐢𝐯𝐞𝐫 • 𝐌𝐨𝐝𝐞𝐫𝐧 𝐃𝐚𝐭𝐚 𝐒𝐭𝐚𝐜𝐤 Snowflake + Databricks + dbt + Airflow + Fivetran + AWS Glue for scalable, testable, version-controlled ELT pipelines. • 𝐂𝐥𝐨𝐮𝐝 𝐌𝐢𝐠𝐫𝐚𝐭𝐢𝐨𝐧𝐬 Teradata, Oracle, SQL Server, Pentaho, Informatica → Snowflake, Redshift, Databricks, BigQuery. • 𝐄𝐓𝐋 / 𝐄𝐋𝐓 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 AWS Glue, Airflow, Informatica, Talend, Pentaho, Azure Data Factory, SSIS, Spark, PySpark. • 𝐃𝐚𝐭𝐚 𝐖𝐚𝐫𝐞𝐡𝐨𝐮𝐬𝐞𝐬 & 𝐋𝐚𝐤𝐞𝐡𝐨𝐮𝐬𝐞𝐬 Snowflake, Databricks, Redshift, BigQuery, Delta Lake, Unity Catalog, Dimensional Modeling. • 𝐀𝐈 & 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 Predictive Analytics, Forecasting, Classification, Recommendation Systems, MLOps, MLflow, SageMaker, TensorFlow, PyTorch, Scikit-Learn. • 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐬 & 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 OpenAI, Claude, Gemini, LangChain, LangGraph, CrewAI, AutoGen, MCP, AI Agents, Autonomous Workflows, Multi-Agent Systems. • 𝐑𝐀𝐆 & 𝐊𝐧𝐨𝐰𝐥𝐞𝐝𝐠𝐞 𝐒𝐲𝐬𝐭𝐞𝐦𝐬 Vector Databases, Pinecone, Weaviate, Qdrant, ChromaDB, Supabase Vector, Enterprise Knowledge Bases, Semantic Search. • 𝐕𝐨𝐢𝐜𝐞 𝐀𝐈 & 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐒𝐲𝐬𝐭𝐞𝐦𝐬 Vapi, Retell AI, ElevenLabs, Twilio, Voice Agents, AI Call Centers, Lead Qualification Systems. • 𝐁𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐏𝐫𝐨𝐜𝐞𝐬𝐬 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 n8n, Make, Zapier, HubSpot, Salesforce, GoHighLevel, CRM Automation, Workflow Automation. • 𝐁𝐈 & 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 Power BI, Tableau, Sigma, Looker, Grafana, Executive Dashboards, Self-Service Analytics. • 𝐃𝐚𝐭𝐚 𝐐𝐮𝐚𝐥𝐢𝐭𝐲 & 𝐎𝐛𝐬𝐞𝐫𝐯𝐚𝐛𝐢𝐥𝐢𝐭𝐲 Great Expectations, dbt Tests, CI/CD, Data Validation Frameworks, Monitoring & Alerting. → 𝐂𝐨𝐫𝐞 𝐓𝐞𝐜𝐡 𝐒𝐭𝐚𝐜𝐤 𝐃𝐚𝐭𝐚 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦𝐬: Snowflake, Databricks, Redshift, BigQuery, Delta Lake, Unity Catalog 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠: dbt, Airflow, AWS Glue, Informatica, Talend, Pentaho, Fivetran, Kafka, Spark, PySpark 𝐀𝐈 / 𝐋𝐋𝐌𝐬: OpenAI, Claude, Gemini, LangChain, LangGraph, CrewAI, AutoGen, MCP 𝐀𝐈 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧: n8n, Make, Zapier, HubSpot, Salesforce, GoHighLevel 𝐕𝐞𝐜𝐭𝐨𝐫 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞𝐬: Pinecone, Weaviate, Qdrant, ChromaDB, pgvector, Supabase Vector 𝐂𝐥𝐨𝐮𝐝: AWS, Azure, GCP, Docker, Kubernetes, Terraform 𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞𝐬: Python, SQL, PySpark, JavaScript, TypeScript, Java, C# 𝐃𝐚𝐭𝐚𝐛𝐚𝐬𝐞𝐬: PostgreSQL, MySQL, SQL Server, Oracle, MongoDB, DynamoDB → 𝐑𝐞𝐬𝐮𝐥𝐭𝐬 𝐈’𝐯𝐞 𝐃𝐞𝐥𝐢𝐯𝐞𝐫𝐞𝐝 • Reduced enterprise ETL runtimes from 6+ hours to under 45 minutes through cloud-native data architectures. • Built Snowflake + dbt + Airflow ecosystems integrating 120+ data sources powering executive dashboards and AI-driven decision systems. • Delivered real-time MLS ingestion platforms processing data from 500+ providers and supporting AI-powered marketing systems. • Built AI voice agents capable of automated lead qualification, appointment booking, and customer engagement. • Developed RAG systems that transformed thousands of documents into searchable enterprise knowledge platforms. • Implemented AI workflow automation that reduced manual operations by up to 80% across sales, support, and operations teams. → 𝐈’𝐦 𝐀 𝐒𝐭𝐫𝐨𝐧𝐠 𝐅𝐢𝐭 𝐈𝐟 𝐘𝐨𝐮 𝐍𝐞𝐞𝐝 • Snowflake or Databricks implementation from scratch • Legacy ETL modernization and cloud migration • Data warehouse or lakehouse architecture • AI Agents and business process automation • RAG applications and enterprise knowledge systems • Voice AI solutions and conversational agents • n8n or Make workflow automation • Machine learning pipelines and MLOps • A senior data engineer or AI engineer to lead delivery and mentor internal teams 📩 Message me with a short description of your data stack, AI initiative, or business process challenge, and I'll provide a candid assessment of scope, architecture, timeline, and the best path forward.

I'm a results-driven Senior Data Engineer specializing in building cloud-native data pipelines and architectures that transform raw data into actionable business insights. With 100% job satisfaction and a 5-star rating, I deliver solutions that exceed expectations. What I Bring: Cloud Expertise: Azure, GCP, and AWS with deep experience in Databricks, BigQuery, and Data Factory Real-Time Processing: Built streaming pipelines reducing reporting latency from hours to minutes Enterprise Scale: Consolidated 50+ data sources, processed 100M+ daily transactions, and supported 1000+ users Architecture Design: Expert in Lakehouse, Medallion, and Star Schema implementations with strong data governance Proven Results: Reduced reporting latency by 98% through real-time pipeline optimization Improved query performance by 40% with strategic data modeling Achieved 35% increase in compliance reporting accuracy Delivered zero-downtime deployments with automated CI/CD I partner closely with stakeholders to understand business needs and deliver data solutions that drive decision-making. Whether it's building real-time analytics platforms, implementing data governance, or optimizing existing pipelines, I focus on scalable, maintainable solutions. Let's discuss how I can help transform your data into a strategic asset.

Data is as valuable as the decisions it enables. Is your leadership team waiting weeks for reports? Are your data pipelines constantly breaking, or is your cloud spend spiraling out of control? I don't just "write ETL", I build the scalable, automated engines that turn raw, messy data into real-time business intelligence. With over 6,000+ hours on Upwork and a 100% Job Success Score, I help enterprises move from manual data chaos to a streamlined, modern data stack. My Core Focus: - Microsoft Fabric: End-to-end implementation (OneLake, Data Factory, Lakehouse/Warehouse). - Databricks: Building robust Medallion architectures using Spark, Delta Lake, and Unity Catalog. - Automated ETL/ELT: Designing resilient pipelines with Airflow, Azure Data Factory, and Python. - Enterprise BI: High-performance Power BI dashboards using Direct Lake and advanced DAX. Why Clients Choose Me: I bridge the gap between technical complexity and business ROI. Whether you are migrating from legacy SQL servers to the cloud or optimizing a complex Databricks environment, I focus on two things: Performance and Clarity. Technical Ecosystem: - Languages: Python, SQL, PySpark, DAX - Platforms: Microsoft Fabric, Azure Synapse, Databricks, Snowflake - Tools: Airflow, ADF, Power BI, Tableau, PostgreSQL/MySQL Ready to transform your data infrastructure into a strategic asset? Click the "Message" or "Book Consultation" button, and let’s discuss your architecture.