Hire the Best Apache NiFi Developers

I help healthcare organizations design, fix, and deliver real-world interoperability solutions - not just theoretical HL7/FHIR/IHE implementations. With 15+ years of hands-on experience, I've built and deployed integrations across HL7v2, HL7v3, C-CDA, FHIR, and IHE for more than 50 organizations worldwide. I work directly at the message level - transformations, mappings, validation, conformance, and troubleshooting - using tools like Mirth Connect, Apache NiFi, and Smile CDR. Many clients come to me when: • integrations don't work as expected • FHIR implementations become too complex • HL7 mappings break across systems • conformance and validation issues block go-live I don't just advise - I build, debug, and deliver working solutions. What makes me different • Author of HL7 v2/v3 specifications and profiles • Contributor to early HL7 FHIR (STU3) • Primary author for Canadian Core/Baseline FHIR profiles • published books and multiple training courses on HL7/FHIR • All HL7 certifications + IHE + SNOMED CT training up to Authoring Level 1 I work at the intersection of specification and implementation - where standards meet real systems. What I can help you with: • HL7v2 / HL7v3 interface development and troubleshooting • FHIR API design, profiling, and implementation • HL7v2 ↔ FHIR transformations (ADT, ORU, OML, etc.) • FHIR ↔ OMOP transformations • C-CDA parsing, generation, validation and C-CDA ↔ FHIR transformation • Integration engine development (Mirth Connect, Apache NiFi) • Conformance testing and validation (HL7v2/v3, FHIR, C-CDA) • Fixing broken integrations and production issues • Implementation Guides (IG), FSH, SUSHI • IHE / HIE integrations (XDS, XCA, XCPD, etc.) Technical stack: • FHIR (R4, STU3), HL7 v2/v3, C-CDA, IHE • Mirth Connect, Apache NiFi, Smile CDR, Aidbox • Java, JavaScript, Python, React, SQL, XML, XSLT, Schematron • Touchstone, Simplifier, Forge, IG Publisher AI & Automation (Applied to Healthcare Interoperability) • Multi-agent AI workflows for healthcare data transformation and validation • LLM-assisted HL7/FHIR mapping and interface documentation • AI-driven data quality analysis and anomaly detection in healthcare messages • Automation of conformance testing and validation workflows using LLM-based agents • Use of AI tools to accelerate implementation guide development and integration debugging Certifications • HL7 FHIR Advanced Developer • HL7 FHIR Foundational Implementer • HL7 FHIR R4 Proficiency • HL7 v2 Control Specialist • HL7 CDA Specialist • HL7 v3 RIM Specialist • IHE Certified Professional • SNOMED CT Terminology Services Let's work! If you need someone who understands both the standard and the implementation, I can help you move faster and avoid costly mistakes.

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!

NEED PRODUCTION-READY, FUNCTIONAL CAD MODELS OPTIMIZED FOR 3D PRINTING? Coming from a background in enterprise software engineering (with an MS in Computer Science), I bring a developer's mindset to 3D CAD design. I don't just sculpt shapes—I engineer functional, parametric systems. My main focus is creating clean, reliable models built specifically for FDM printing. I know firsthand how critical printability, tight tolerances, and mechanical fits are, so I design parts that work perfectly right off the build plate. I treat CAD design like writing production-grade code. When you work with me, you get: ▪ TRUE PARAMETRIC DESIGN: Models built so you can easily tweak and update dimensions by changing a few simple values. ▪ CLEAN ARCHITECTURE: A tidy file structure and a logical, easy-to-read model history timeline. ▪ END-TO-END SUPPORT: I don't just hand over a file. I am happy to advise on slicing settings, material choices, and print optimization to make sure you get the best physical result. I publish my independent work under the "Void to Solid" name (feel free to check out these models in my Upwork portfolio). If you have a sketch, a technical requirement, or just a rough idea in mind—feel free to reach out. Let's discuss how we can bring it to life.

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

With over two decades of experience encompassing DevOps engineering and data engineering, I specialize in architecting robust infrastructure and optimizing data workflows to drive organizational success. My career highlights include designing and implementing CI/CD pipelines, managing diverse cloud environments, and executing complex data migration and ETL processes with a focus on scalability and performance. 𝙆𝙚𝙮 𝙎𝙠𝙞𝙡𝙡𝙨: 𝗖𝗹𝗼𝘂𝗱 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺𝘀: AWS, Azure, GCP, Oracle Cloud, Cloudflare, Hetzner, DigitalOcean 𝗜𝗻𝗳𝗿𝗮𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 𝗮𝘀 𝗖𝗼𝗱𝗲: Terraform, CloudFormation, Ansible 𝗖𝗜/𝗖𝗗: Jenkins, GitLab CI/CD, CircleCI 𝗖𝗼𝗻𝘁𝗮𝗶𝗻𝗲𝗿 𝗢𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻: Kubernetes, Docker Swarm, ECS 𝗠𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴 𝗮𝗻𝗱 𝗔𝗹𝗲𝗿𝘁𝗶𝗻𝗴: Prometheus, Grafana, ELK Stack, Nagios 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗮𝗻𝗱 𝗖𝗼𝗺𝗽𝗹𝗶𝗮𝗻𝗰𝗲: TLS/SSL, OAuth, PCI DSS, GDPR 𝗡𝗲𝘁𝘄𝗼𝗿𝗸𝗶𝗻𝗴: OpenVPN, IPsec, Cisco ASA 𝗩𝗶𝗿𝘁𝘂𝗮𝗹𝗶𝘇𝗮𝘁𝗶𝗼𝗻: Proxmox, VMware, VirtualBox 𝗪𝗲𝗯 𝗦𝗲𝗿𝘃𝗲𝗿𝘀: Nginx, HAProxy, Apache HTTP Server 𝗗𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗲𝗱 𝗦𝘁𝗼𝗿𝗮𝗴𝗲: Ceph, GlusterFS, Amazon EFS 𝗖𝗼𝗺𝗺𝘂𝗻𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗣𝗿𝗼𝘁𝗼𝗰𝗼𝗹𝘀: WebSocket, MQTT, AMQP 𝗗𝗮𝘁𝗮𝗯𝗮𝘀𝗲 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁: PostgreSQL, MySQL, Oracle, MongoDB, Cassandra 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲𝘀: SQL, Python, Java 𝗕𝗶𝗴 𝗗𝗮𝘁𝗮 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝗶𝗲𝘀: Hadoop, Spark, Kafka 𝗕𝗜 & 𝗗𝗮𝘁𝗮 𝗪𝗮𝗿𝗲𝗵𝗼𝘂𝘀𝗶𝗻𝗴: Azure Data Lake, Power BI, ClickHouse 𝗗𝗮𝘁𝗮 𝗚𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲: Implementing governance frameworks for data quality and compliance 𝙋𝙧𝙤𝙟𝙚𝙘𝙩 𝙃𝙞𝙜𝙝𝙡𝙞𝙜𝙝𝙩𝙨: 𝗪𝗘𝗣𝗔 𝗣𝗿𝗼𝗷𝗲𝗰𝘁: Orchestrated Azure cloud infrastructure setup, implemented robust data pipelines with Kibana, Flink, Kafka, and Power BI. Managed data aggregation from 13+ factory locations, enabling centralized processing and analysis. 𝗥𝗚𝗧𝗡 𝗣𝗿𝗼𝗷𝗲𝗰𝘁: Established comprehensive monitoring services, conducted infrastructure maintenance, and managed server upgrades across multiple environments. Utilized Prometheus, Grafana, MySQL, and Proxmox to optimize system performance and ensure high availability. 𝗗𝗶𝗴𝗶𝘁𝗮𝗹 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻 𝗜𝗻𝗶𝘁𝗶𝗮𝘁𝗶𝘃𝗲𝘀: Led initiatives integrating DevOps and data engineering principles to streamline deployment processes and enhance data-driven decision-making capabilities. Implemented advanced analytics solutions and data lakes for optimized data processing and integration. 𝙒𝙤𝙧𝙠 𝘼𝙥𝙥𝙧𝙤𝙖𝙘𝙝: Dedicated to delivering high-quality solutions aligned with client objectives, I excel in collaborative environments where I leverage my expertise to innovate and optimize infrastructure and data workflows. My proactive approach and commitment to continuous learning ensure I stay ahead in evolving technologies. 𝙇𝙚𝙩'𝙨 𝘾𝙤𝙣𝙣𝙚𝙘𝙩: If you're looking for a seasoned professional who can optimize your infrastructure, streamline deployment and data processes, and ensure scalability and security across your projects, I'm eager to discuss how I can contribute to your organization’s success.

Messy data slowing your team down? I build scalable ETL/ELT pipelines and modern cloud architectures on Azure, Databricks, Fabric, and Snowflake that turn raw, chaotic data into clean, analytics-ready systems fast and reliably. I bridge the gap between fragmented data sources and production-grade dashboards, seamlessly adapting to your existing infrastructure rather than forcing an expensive rebuild. What I Can Help You With: Data Warehouse & Lakehouse Architecture: Implementing Medallion design patterns (Bronze → Silver → Gold) using Delta Lake, Microsoft Fabric OneLake, and Snowflake. Scalable ETL/ELT Ingestion: Building automated, metadata-driven pipelines via Azure Data Factory, Fabric Pipelines, Databricks (PySpark/SQL), and dbt. Real-Time Data Streaming: Architecting low-latency workflows using Apache Kafka, Azure Event Hubs, and streaming engines. Database Design & Optimization: Performance tuning, indexing, and data modeling for PostgreSQL, Azure SQL, and cloud warehouses. Proven Project Highlights: Microsoft Fabric Incremental Pipeline: Built a control-table pattern using Get Metadata, Lookup, and ForEach loops to orchestrate zero-duplicate, quarterly ingestion from SharePoint into OneLake via Dataflow Gen2. Azure/Databricks Streaming: Developed a restaurant analytics platform processing 80,000+ events/day, cutting reporting lag from 6 hours to under 3 minutes. Kafka/Snowflake Pipeline: Engineered a real-time stock market data pipeline tracking 120+ tickers with under 8 seconds end-to-end latency. I write clean, documented code your team can maintain long-term and provide transparent daily updates. Message me with your data challenge and I’ll walk you through exactly how to solve it.