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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.

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.

Database Development : ****************************************** Oracle Sql, Plsql, Data Export from Oracle DB to excel MSSQL PostgreSQL AWS Redshift, Glue, S3 GCP BigQuery Snowflake Oracle Forms(D2k) Expertise in Entities like : ------------------------------- Tables, Views, Sql Queries, All Types of JOINS, Cursor, Procedure, Function, Packages, Triggers, Collection, Bulk Collect, Analytical/Window Function, Dynamic Sqls, Pipelined Functions, Sql Loader, External Table, Hints, Bug Fixing , Debugging, Impact Analysis etc. DBA ************** * Having 10+years of experience as an Oracle, MICROSOFT SQL server and Golden Gate administrations in Banking, finance, Healthcare, Multimedia and currently working in Telecom domain. Working in 24x7 environments and providing support. * 6 +Month experience on AWS RDS and EC2 instances. Experience in RAC Implementation, maintenance of Clustered Databases, CRS upgrade, ASM implementation and maintenance. * Hands on knowledge of Golden gate replication and online Migrations tool. * Migration from 11g and 2c to 19c using DBUA Experience in installation & configuration oracle 10g, 11g, 12c and 19c RAC. * Implementation MICROSOFT SQL server 2008, 2012, 2014 and 2016 in development, test, and production environment. Always on replication. * Monitoring MSSLQL Server clustering, Log shipping, mirroring * Having dept knowledge about Oracle and MICROSOFT SQL server patching. * Tested and Implemented different physical and logical backup and recovery methods like point in time, Media recovery, RMAN and EXPDP and IMPDP utility. * Experience in designing Data guard solution and implementation and in managing physical standby. * Experience in monitoring and optimizing the Database performances through tuning using stats pack, AWR, ADDM, explain plan, Backup timings of databases. Having hands-on knowledge Oracle Table Partitions and Materialized Views. * Upgraded/ Migrated MICROSOFT SQL server Instances/Databases from older version MICROSOFT SQL server to new version of SQL Server. Apply SP (Service Pack)/ hot fixes on MSSQL server Instances to address security and upgraded related issues. * Performance Tuning and schedule jobs to automate different database related activities including backup, monitoring database health, disk space, and backup verification. * Extensive knowledge of oracle architecture SGA, PGA, Listener, tns names. * Developed Different Maintenance Plans for database monitoring. Setup Jobs, Maintenance plans for backups. Rebuilding indexes, check server health, alert, notifications Manual, on demand and setup jobs for Database Backup, and design backup strategy. * Experience in Mirroring and Log shipping and managing Standby Databases. * Creating File groups & managing File groups. Creating users and providing proper privileges for Database access. * Memory monitoring and optimizing the Database Performances through Tuning Explain Plan. Experience in Oracle RMAN backup (Full, incremental and cumulative) and recovery, Incomplete recovery and disaster recovery. * Experience in, Maintenance plans for backups, Rebuilding indexes, check server health, alert, notifications Manual, on Demand and setup jobs for Database Backup, and design backup strategy. * Hands-on experience in configuring MSSQL server and Windows system event log entries for warnings. Language : ********************* Python (Pandas, Numpy, Matplotlib, AI/ML, PySpark) Java (Java, Spring MVC, Spring boot, Microservices, Rest-api, React, Angular old version Javascript) ETL: Informatica,ODI **************** 1. Proficient in data integration and ETL processes using Informatica PowerCenter. 2. Extensive experience in designing, developing, and implementing ETL solutions with a focus on Informatica PowerCenter. 3. Demonstrated expertise in creating complex mappings, workflows, and transformations in Informatica PowerCenter to optimize data flow. 4.Proven track record of troubleshooting Informatica PowerCenter workflows. 5. In-depth knowledge of working with various databases and sources like oracle , terafata, flat files to extract, transform, and load data using Informatica PowerCenter. 6. Implemented and maintained data warehouses utilizing Informatica PowerCenter as a key component of the ETL architecture. 7. Proficient in utilizing Informatica PowerCenter for handling large volumes of data. Excel : ************* Advanced Excel Formula, Macro Data Visualization : ************************** Power BI, As a Trainer to Train in SQL Help Students in their SQL Assignments ####################################### Having over 14 Years of experience mainly as a Database Development Expert. Also having hands on experience in above mentioned skill set. Just give a faith for your development activities, I assure you will not be disappointed. Note : Pay after only the satisfaction of work only. Thanks DK Raju

𝐈 𝐛𝐮𝐢𝐥𝐝 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧-𝐠𝐫𝐚𝐝𝐞 𝐝𝐚𝐭𝐚 𝐩𝐥𝐚𝐭𝐟𝐨𝐫𝐦𝐬 𝐟𝐨𝐫 𝐜𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 𝐝𝐞𝐚𝐥𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐛𝐫𝐨𝐤𝐞𝐧 𝐩𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬, 𝐬𝐜𝐚𝐭𝐭𝐞𝐫𝐞𝐝 𝐬𝐲𝐬𝐭𝐞𝐦𝐬, 𝐬𝐥𝐨𝐰 𝐫𝐞𝐩𝐨𝐫𝐭𝐢𝐧𝐠, 𝐚𝐧𝐝 𝐮𝐧𝐫𝐞𝐥𝐢𝐚𝐛𝐥𝐞 𝐦𝐞𝐭𝐫𝐢𝐜𝐬. I’m a Senior Data Engineer with 10+ years of experience building cloud data platforms, ETL/ELT pipelines, lakehouses, warehouses, and analytics-ready data layers using Microsoft Fabric, Snowflake, AWS, BigQuery, dbt, Python, SQL, Airflow, Fivetran, Airbyte, and Databricks. My focus is not just moving data from point A to point B. I design reliable data systems that are automated, scalable, well-modeled, and trusted by business teams. 𝐖𝐡𝐚𝐭 𝐈 𝐡𝐞𝐥𝐩 𝐰𝐢𝐭𝐡 ✅ 𝐌𝐢𝐜𝐫𝐨𝐬𝐨𝐟𝐭 𝐅𝐚𝐛𝐫𝐢𝐜 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 Lakehouse, Warehouse, Dataflows Gen2, pipelines, notebooks, semantic models, Medallion architecture, and Power BI-ready data layers. ✅ 𝐂𝐥𝐨𝐮𝐝 𝐃𝐚𝐭𝐚 𝐖𝐚𝐫𝐞𝐡𝐨𝐮𝐬𝐞 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 Snowflake, BigQuery, Redshift, Databricks, PostgreSQL, SQL Server, and Azure Synapse architecture. ✅ 𝐄𝐓𝐋/𝐄𝐋𝐓 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 API ingestion, database replication, SaaS integrations, file ingestion, batch jobs, incremental loads, and scheduled workflows. ✅ 𝐝𝐛𝐭 & 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 Staging, intermediate, marts, incremental models, tests, documentation, metric definitions, and business logic standardization. ✅ 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 & 𝐎𝐫𝐜𝐡𝐞𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧 Airflow, Dagster, AWS Lambda, Glue, Step Functions, ADF, CI/CD, monitoring, retries, alerts, and production workflow automation. ✅ 𝐃𝐚𝐭𝐚 𝐐𝐮𝐚𝐥𝐢𝐭𝐲 & 𝐆𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞 Deduplication, reconciliation, schema drift handling, validation rules, MDM, Golden Record logic, RBAC, access control, and audit-ready reporting layers. 𝐑𝐞𝐜𝐞𝐧𝐭 𝐩𝐫𝐨𝐣𝐞𝐜𝐭 𝐞𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞: 𝐌𝐢𝐜𝐫𝐨𝐬𝐨𝐟𝐭 𝐅𝐚𝐛𝐫𝐢𝐜 𝐞𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞 𝐚𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 𝐩𝐥𝐚𝐭𝐟𝐨𝐫𝐦 Built a centralized Fabric platform with Lakehouse, Warehouse, Dataflows, pipelines, semantic models, and Power BI reporting layers for a global organization with fragmented reporting sources. 𝐍𝐞𝐚𝐫 𝐫𝐞𝐚𝐥-𝐭𝐢𝐦𝐞 𝐒𝐧𝐨𝐰𝐟𝐥𝐚𝐤𝐞 𝐝𝐚𝐭𝐚 𝐩𝐥𝐚𝐭𝐟𝐨𝐫𝐦 Designed operational pipelines into Snowflake with incremental ingestion, schema change handling, deduplication, retries, and reliable dbt-based reporting models. 𝐌𝐨𝐝𝐞𝐫𝐧 𝐒𝐚𝐚𝐒 𝐝𝐚𝐭𝐚 𝐬𝐭𝐚𝐜𝐤 Centralized HubSpot, Stripe, GA4, Google Ads, Salesforce, MongoDB, and product data into BigQuery/Snowflake using Fivetran, Airbyte, dbt, Dagster, and Metabase. 𝐋𝐞𝐠𝐚𝐜𝐲 𝐦𝐢𝐠𝐫𝐚𝐭𝐢𝐨𝐧 𝐭𝐨 𝐜𝐥𝐨𝐮𝐝 𝐰𝐚𝐫𝐞𝐡𝐨𝐮𝐬𝐞 Led migrations from SQL Server, SAP BW, Oracle, Hadoop, and on-prem systems into modern cloud warehouses with optimized performance and automated workflows. 𝐀𝐖𝐒 𝐝𝐚𝐭𝐚 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 Built automated workflows using S3, Lambda, Glue, Step Functions, IAM, SNS, CloudWatch, and Python to reduce manual reporting and improve pipeline reliability. 𝐓𝐨𝐨𝐥𝐬 𝐈 𝐰𝐨𝐫𝐤 𝐰𝐢𝐭𝐡 Microsoft Fabric, Snowflake, BigQuery, Redshift, Databricks, Azure Synapse, PostgreSQL, SQL Server, Oracle, SAP BW, Hadoop, dbt, Python, SQL, Airflow, Dagster, Fivetran, Airbyte, ADF, SSIS, Talend, AWS S3, Lambda, Glue, Step Functions, IAM, SNS, CloudWatch, Power BI, Tableau, Metabase, and Looker. You should reach out if you need a senior data engineer to: ✅ Build a cloud data warehouse or lakehouse ✅ Migrate legacy systems to Snowflake, Fabric, BigQuery, or AWS ✅ Fix unreliable ETL/ELT pipelines ✅ Design dbt models and trusted reporting layers ✅ Automate manual reporting workflows ✅ Integrate APIs, CRMs, ERPs, databases, and SaaS platforms ✅ Build production-ready data infrastructure for analytics and BI If your data stack is messy, slow, or hard to trust, send me a message. I’ll help you map the cleanest path from scattered systems to a reliable data platform.

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

🏆 TOP RATED PLUS || Top 1% on Upwork || 8+ Years of Experience || 100% Job Success || Expert Vetted Most data teams are held back by unreliable pipelines, untrustworthy warehouses, and data infrastructure 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 (SF, BQ, 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 ⭐ "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 identified the bottlenecks, restructured the workflow logic, and reduced 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 trustworthy, send a quick message about your project, and I'll take it from there.