Hire the Best Databricks MLflow Specialists

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

A Senior Data Engineer with 8+ years of experience building reliable, scalable data pipelines and infrastructure, from data ingestion and transformation through warehousing, streaming, and data analytics with dbt, Snowflake, Airflow across AWS, Azure, and GCP with robust ETL and ELT. 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!

You probably think clicking "deploy" on Databricks from the cloud marketplace is all it takes to build a modern data stack. Instead, you get unmanageable infrastructure, skyrocketing costs, and pipelines feeding reports nobody trusts. 𝗜 𝗳𝗶𝘅 𝘁𝗵𝗮𝘁. 𝗡𝗼 𝗮𝗴𝗲𝗻𝗰𝗶𝗲𝘀, 𝗻𝗼 𝗯𝗹𝗼𝗮𝘁. Just a multi-certified, 5+ years of experience Cloud Solutions Architect building automated, high-integrity platforms that turn raw data into a competitive advantage. If you shoot me a invitation or message I'll send you a personalized Loom video back on how I may be able to help you; and of course, to prove that I'm the real deal, 𝗻𝗼 𝗔𝗜 𝗶𝗻𝘃𝗼𝗹𝘃𝗲𝗱! Whether you are building a greenfield lakehouse from scratch or migrating legacy systems to the cloud, I architect efficient, cost-effective environments that scale without the overhead. I understand the business bottom line just as well as the underlying code. ✪ 100% Job Success Score | 5.0★ average ✪ Proven experience on multi-cloud architectures 💡 𝗪𝗵𝗮𝘁 𝗜 𝗱𝗼: • 𝗗𝗮𝘁𝗮 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴: I build production-ready environments using Terraform. No manual marketplace or standard deployments that break at scale. • 𝗥𝗲𝗹𝗶𝗮𝗯𝗹𝗲 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴: Raw data becomes actionable. I build resilient Medallion architectures and automated ETL/ELT pipelines so your stakeholders actually trust the numbers. • 𝗣𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝗠𝗟𝗢𝗽𝘀: I bridge the gap between data engineering and machine learning. Using MLflow and Databricks Model Serving, I operationalize models into scalable, real-time REST endpoints and automated streaming inference pipelines. • 𝗚𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 & 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆: Proper data governance utilizing Unity Catalog (no legacy Hive metastores) to ensure your data is accessible, secure, and future-proof. • 𝗖𝗹𝗼𝘂𝗱 𝗖𝗼𝘀𝘁 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻: Most companies overspend on cloud infrastructure. I architect systems that pay for themselves in weeks by eliminating overhead and inefficiencies with efficient auditing and monitoring features. ✅ 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 (𝘃𝗲𝗿𝗶𝗳𝗶𝗲𝗱): • Databricks Professional Data Engineer • Databricks Associate Data Engineer • Databricks Lakehouse Fundamentals • GCP Professional Data Engineer • GCP Associate Cloud Engineer • GCP Cloud Digital Leader • AWS Associate Solutions Architect • AWS Cloud Practitioner 🔧 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 𝘄𝗶𝘁𝗵 𝗖𝗹𝗼𝘂𝗱 𝗦𝗲𝗿𝘃𝗶𝗰𝗲𝘀: • 𝗗𝗮𝘁𝗮𝗯𝗿𝗶𝗰𝗸𝘀: Workflows, LDP (Lakeflow Declarative Pipelines), Unity Catalog, Workflows, Databricks SQL, MLFlow. • 𝗔𝗺𝗮𝘇𝗼𝗻 𝗪𝗲𝗯 𝗦𝗲𝗿𝘃𝗶𝗰𝗲 (𝗔𝗪𝗦): EMR, Athena, Redshift, Glue, S3, RDS, Kinesis Data Firehose, Kinesis, and Data Streams. • 𝗚𝗼𝗼𝗴𝗹𝗲 𝗖𝗹𝗼𝘂𝗱 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺 (𝗚𝗖𝗣): Bigquery, Dataform, Composer, Dataflow, Dataproc, Cloud Storage, Pub/Sub, Cloud Functions, and Looker Studio. • 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗔𝘇𝘂𝗿𝗲: Data Factory, Synapse, and Storage Account. • 𝗢𝘁𝗵𝗲𝗿𝘀: Terraform, dbt, Airflow, Airbyte, Hadoop, and Hive. ⚙️ 𝗖𝗼𝗿𝗲 𝗲𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲: • 𝗥𝗼𝗹𝗲𝘀: Data Architect, Data Engineer, Solutions Architect, Platform Engineer • 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺𝘀: Databricks (Delta Lake, Unity Catalog, Lakeflow, Workflows), BigQuery • 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲: Infrastructure as Code (IaC), Terraform, Multi-Cloud (AWS, GCP, Azure) • 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲: Medallion Architecture, Data Lakehouse, Data Governance, Data Quality, Machine Learning • 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴: PySpark, Python, SQL, dbt, Apache Airflow, ETL/ELT, CDC, Batch and Stream Processing

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.

✅ 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.

Most Azure data teams are stuck with brittle pipelines, SSIS packages nobody wants to touch, and Fabric migrations that stalled halfway. That's exactly what I fix. 𝗔𝗗𝗙 | 𝗗𝗮𝘁𝗮𝗯𝗿𝗶𝗰𝗸𝘀 | 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗙𝗮𝗯𝗿𝗶𝗰 | 𝗦𝘆𝗻𝗮𝗽𝘀𝗲 | 𝗦𝗻𝗼𝘄𝗳𝗹𝗮𝗸𝗲 | 𝗟𝗼𝗴𝗶𝗰 𝗔𝗽𝗽𝘀 | 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 | 𝗔𝗜 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 ────────────────────────────── As a Senior Azure Data Engineer with 8+ years of experience, I don't just build ADF pipelines and call it done. I architect end-to-end data systems — from multi-source ingestion through Microsoft Fabric Lakehouse and Medallion Architecture to Power BI reporting — built for scale, fault tolerance, and AI readiness. 100% Job Success Score · Top Rated on Upwork · US enterprise clients · Microsoft partner teams · Finance, Healthcare & Retail ────────────────────────────── → 𝗪𝗵𝗲𝗿𝗲 𝗜 𝗺𝗮𝗸𝗲 𝘁𝗵𝗲 𝗯𝗶𝗴𝗴𝗲𝘀𝘁 𝗶𝗺𝗽𝗮𝗰𝘁 • Built ADF + Databricks pipelines processing 𝗯𝗶𝗹𝗹𝗶𝗼𝗻𝘀 𝗼𝗳 𝗿𝗼𝘄𝘀 for US enterprise clients — fast single-record retrieval under milliseconds • Designed Medallion Architecture automating 𝟭𝟰𝟬+ 𝗱𝗮𝗶𝗹𝘆 𝗳𝗶𝗹𝗲𝘀 (CSV, Excel, Fixed-Width) at Fintexinc Canada • Reduced manual effort by 𝟲𝟬% via ADF + PySpark + Synapse automation at Capgemini • Cut manual reporting effort by 𝟲𝟬% automating Zoom & CVENT API data pipelines via Logic Apps • Delivered production-ready RAG system on Azure AI Foundry 𝗶𝗻 𝘂𝗻𝗱𝗲𝗿 𝟮 𝗱𝗮𝘆𝘀 — hybrid semantic + keyword retrieval • Collaborated directly with 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 to build Purview as a Service — enterprise-scale governance automation ────────────────────────────── 𝗪𝗵𝗮𝘁 𝗜 𝗕𝘂𝗶𝗹𝗱 𝗪𝗶𝘁𝗵 🗄️ Warehouses, Lakehouses & Data Lakes: Microsoft Fabric Lakehouse, Azure Synapse Analytics, Databricks, Snowflake, ADLS Gen2, Delta Lake ⚙️ Pipelines & Orchestration: Azure Data Factory (ADF), Synapse Pipelines, Fabric Data Factory, Databricks Workflows 🔄 Transformation: PySpark, Apache Spark, Python, SQL, Medallion Architecture (Bronze/Silver/Gold), Star Schema 📨 Streaming & Real-Time: Azure Event Hubs, Fabric Eventstream, Azure Stream Analytics 🔗 Migrations & Integrations: SSIS → ADF, on-prem to Azure, SAP ECC/Hana, Salesforce, Oracle, MySQL, PostgreSQL, MongoDB, CDC pipelines ⚡ Automation: Logic Apps, Power Automate, Azure Function Apps 🤖 AI & RAG: Azure OpenAI, Azure AI Foundry, RAG pipelines, AI agents, Azure Cognitive Search, Prompt Engineering ☁️ Cloud & Infra: Microsoft Azure, ADLS, Azure Key Vault, Azure Monitor, Azure DevOps 🐍 Languages: Python, PySpark, SQL (T-SQL, views, procedures, functions), REST APIs 🗃️ Databases: SQL Server, Snowflake, MongoDB, PostgreSQL, MySQL, Oracle, Dataverse 📊 BI & Reporting: Power BI, KQL, Azure Log Analytics, Azure Data Explorer 🏛️ Governance: Microsoft Purview — cataloging, lineage, GDPR/HIPAA compliance 🛠️ Dev Tools: GitHub, Azure DevOps, drawio, Visio, Postman ────────────────────────────── 𝗪𝗵𝗮𝘁 𝗜 𝗗𝗲𝗹𝗶𝘃𝗲𝗿 ✅ 𝗔𝗗𝗙 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀 𝗮𝘁 𝗲𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝘀𝗰𝗮𝗹𝗲 — billions of rows, with error handling, retry logic, monitoring, and documented architecture your team can maintain ✅ 𝗦𝗦𝗜𝗦 → 𝗔𝗗𝗙 𝗺𝗶𝗴𝗿𝗮𝘁𝗶𝗼𝗻𝘀 — full package analysis, conversion, testing, and production deployment ✅ 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗙𝗮𝗯𝗿𝗶𝗰 𝗟𝗮𝗸𝗲𝗵𝗼𝘂𝘀𝗲 𝗯𝘂𝗶𝗹𝗱𝘀 — ingestion to Medallion Architecture to Power BI, with lineage and observability built in ✅ 𝗦𝗻𝗼𝘄𝗳𝗹𝗮𝗸𝗲 𝗱𝗮𝘁𝗮 𝘄𝗮𝗿𝗲𝗵𝗼𝘂𝘀𝗶𝗻𝗴 — DWH design, ADF-to-Snowflake pipelines, SQL Server/Oracle cloud migrations ✅ 𝗪𝗼𝗿𝗸𝗳𝗹𝗼𝘄 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 — eliminating manual bottlenecks across business processes and data workflows ✅ 𝗔𝗜-𝗽𝗼𝘄𝗲𝗿𝗲𝗱 𝗱𝗮𝘁𝗮 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 — RAG pipelines, Azure OpenAI chatbots, AI agents grounded on your business data ✅ 𝗖𝗹𝗼𝘂𝗱 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻𝘀 — Salesforce, SAP, Oracle, Snowflake, and SaaS APIs connected into Azure ✅ 𝗗𝗮𝘁𝗮 𝗴𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 — Purview setup, cataloging, lineage, GDPR/HIPAA-aligned pipelines ────────────────────────────── 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝗶𝗲𝘀: Finance & Banking | Healthcare | Retail & E-commerce | FinTech | Enterprise SaaS | Others 𝗔𝘃𝗮𝗶𝗹𝗮𝗯𝗶𝗹𝗶𝘁𝘆: 40+ hrs/week | 0–4 hr response | Open to contract-to-hire ────────────────────────────── 📩 Message me with your Azure data challenge — I respond within 4 hours and will tell you exactly whether and how I can help.