Hire the Best Pyspark Developers

I'm a Senior Data Engineer with 8+ years of strong technical expertise in building reliable and scalable data infrastructure, from data ingestion to transformation to warehousing, streaming, and data analytics, specializing in dbt, Snowflake, Airflow, Databricks (and more) across AWS, Azure, and GCP, with robust ELT and ETL pipelines. 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, AWS Step Functions, 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 governed through the Glue Data Catalog and Lake Formation, with Athena and Redshift Spectrum for serverless queries, Medallion Architecture, partitioning, and performance tuning. ✅ Data Transformation & Modeling: dbt (Core and Cloud), SQLMesh, Spark and PySpark on EMR and AWS Glue, 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 | Athena | Delta Lake | Iceberg ⚡ Transformation: dbt | SQLMesh | Spark | PySpark | AWS Glue | EMR | Star Schema | Medallion Architecture ⚡ Orchestration: Airflow (GCP Cloud Composer and AWS MWAA) | Dagster | Prefect | Azure Data Factory | Step Functions ⚡ Streaming: Kafka | Flink | Kinesis | Pub/Sub | Spark Structured Streaming | ClickHouse ⚡ Ingestion: Fivetran | Airbyte | Matillion | Stitch | Hevo | Meltano | CDC ⚡ Governance & Catalog: Glue Data Catalog | Lake Formation | Unity Catalog | Microsoft Purview | Dataplex ⚡ 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!

A working demo and a system that survives production are two very different things. I build the second kind. Over a decade of backend engineering and 70+ completed projects on Upwork. I run Datum Brain, a software and AI engineering company, so you get one senior engineer accountable end to end, with a team behind him when the work needs it. We ship Go microservices, data pipelines, and LLM systems for FinTech, SaaS, EdTech, and AdTech clients. Recent work: 🛡 Real-time ad fraud detection (TrueAudience) High-concurrency Go backend that scores ad traffic to catch bots before advertisers pay. 80M+ events, under 20ms decisions. Go, TimescaleDB, real-time pipelines. 🏦 Go microservices for an EMI and payments platform (Zolvat) Ledger logic, payment flows, and service orchestration for an installment payments platform. Go, microservices, PostgreSQL. 🎥 WebRTC proctoring infrastructure (Meazure / Examity) Real-time media and session orchestration for thousands of concurrent exam sessions at one of the largest US proctoring providers. Go, WebRTC, LiveKit, NATS. 📊 Big data pipeline optimization (Nike) Cut processing time and compute cost on large PySpark workloads. PySpark, AWS. 📄 Document intelligence platform (Centrum AI) OCR and RAG pipeline that turns unstructured documents into structured, queryable data with human review. Python, FastAPI, LangChain, RAG. What I work with: Backend: Go, Python, FastAPI, gRPC, REST, PostgreSQL, TimescaleDB, Redis, NATS, Kafka Data: PySpark, ETL pipelines, data quality frameworks, AWS, GCP Real-time: WebRTC, LiveKit, event streaming, high-concurrency systems AI and LLM: LangChain, LangGraph, RAG, multi-agent systems, OpenAI, Claude, evals Infra: Docker, Kubernetes, CI/CD, nginx How I work: I scope before I quote, so you know what you are getting and when. I flag risks early instead of at the deadline. Production-ready means tested, documented, monitored, and handed over properly. Good fit if you need something that runs in production and not a proof of concept, you want one senior engineer accountable end to end, and you value clear communication and honest scoping. Not a fit if you are shopping purely on hourly rate, or the spec changes daily and nobody owns decisions. If your backend needs to handle real load, or your data or AI work needs to go from demo to product, send me a message.

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.

Struggling with slow, unreliable data pipelines, rising cloud costs, or a data stack that can't keep up with your AI initiatives? I help businesses fix exactly that. I'm a Senior Data Engineer with hands-on experience helping businesses design, build, and scale reliable data infrastructure across Azure, GCP, and AWS. I specialize in end-to-end ETL/ELT pipelines, real-time data processing, and cloud-native data architecture using PySpark, Python, SQL, Databricks, and BigQuery. Across 21+ completed projects on Upwork, I've delivered more than $100K in data engineering solutions, including systems processing over 10 million records with performance improvements of up to 40%. My work spans automated ingestion frameworks, CRM and analytics integrations, RAG-based LLM pipelines, and cloud cost optimization without sacrificing performance. Clients consistently point to my clear communication, reliability, and commitment to quality, reflected in my 100% Job Success score and Top Rated Plus status. Whether you need a pipeline built from scratch, an existing data stack optimized, or an ongoing data engineering partner, I bring the technical depth and communication needed to get projects delivered on time and on budget. If you have a data challenge, let's connect and discuss how I can help move your project forward.

🏆 Top Rated Plus 🌟 100% Job Success 🤝 Satisfied Clients ⏱ Quick Turnaround 📞 Clear Communication Why work with me? Proven Experience: 💎 Backed by 15+ years of delivering results through scalable, cost-efficient data solutions. Technical Expertise: 💎 AI-Data Architecture: I deliver real-world-ready data through automated, reliable pipelines. The new AI era requires a new data platform. 💎 Conversational Analytics & AI Agents: Enable users to chat with their data through AI-driven interfaces. Google Conversational Analytics API and Gemini Enterprise 💎 Data Visualization: Skilled in Looker, Looker Studio, Power BI, Tableau, Superset, and others. 💎 Data Web Portals: Skilled in developing custom embeddable solutions and full web platforms under your own brand and domain. 💎 Database Management: Expertise in SQL (BigQuery, SQL Server, Oracle, MySQL, PostgreSQL, Snowflake) and NoSQL systems. 💎 ETL: Experience with both streaming and batch pipelines using Airflow, Apache Beam, Kafka, Debezium, Pub/Sub, and others. 💎 Data Modeling: Proficient with dbt, Dataform, and PySpark. 💎 Version Control: Comfortable with Git-based tools (GitHub, Bitbucket, GitLab, Azure DevOps). 💎 Cloud Platforms: Certified and experienced in GCP, AWS, and Azure. 💎 Unstructured Data: JSON, XML, Excel, Google Sheets. 💎 GA4 Data: Google Analytics 4 for advanced analysis. Soft Skills & Work Ethic: 💎 Versatile & Adaptive: Quick to learn new tools, roles, and business domains. 💎 Value-Driven: Focused on delivering high-impact outcomes with cost-efficiency. 💎 Detail-Oriented: Committed to precision and quality in every task. 💎 Reliable & Time-Conscious: Consistent delivery of high-quality work on time. 💎 Leadership: Capable of guiding teams and leading initiatives when needed. 💎 Analytical: Skilled at breaking down complex problems and finding effective solutions. 💎 Collaborative: Strong team player, effective in multidisciplinary environments. Scalable Technical Capacity: I’m supported by a network of 15+ specialists, including Solution and Data Architects, Developers, Designers, Process Specialists, DevOps Engineers, Machine Learning Engineers, Data Scientists, Data Analysts, and more. We work collaboratively to ensure your project receives the strongest possible technical support, from strategy to execution. How I approach projects: - Kick-off meeting to review requirements and deliverables - Action plan development using a project management tool - Weekly demo meetings to showcase progress - Detailed time and task tracking - Continuous feedback loop to ensure alignment and improvement - Complete documentation of the solution

🏆 𝐄𝐱𝐩𝐞𝐫𝐭-𝐕𝐞𝐭𝐭𝐞𝐝 - 𝗧𝗼𝗽 𝟭% 𝗼𝗻 𝗨𝗽𝘄𝗼𝗿𝗸 ✅ 𝟕+ 𝐘𝐞𝐚𝐫𝐬 𝐨𝐟 𝐄𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞 ⏰ 𝟏𝟐𝟎𝟎𝟎 + 𝐔𝐩𝐰𝐨𝐫𝐤 𝐇𝐨𝐮𝐫𝐬 | 𝟏𝟎𝟎+ 𝐏𝐫𝐨𝐣𝐞𝐜𝐭𝐬 𝐃𝐞𝐥𝐢𝐯𝐞𝐫𝐞𝐝 ⭐️ $𝟕𝟎𝟎𝐤+ 𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐨𝐧 𝐔𝐩𝐰𝐫𝐨𝐤 I’m Abdul, an Upwork Certified AI/LLM engineer with 7+ years of experience helping startups and growing teams build smart AI solutions. From autonomous agents, MVPs, AI-native products to intelligent analytics and cloud-ready deployments, I will help scale your operations, workflows, and revenue. —------------------------------------------------------------------- ⭐️𝐓𝐫𝐮𝐬𝐭𝐞𝐝 𝐛𝐲 𝐈𝐧𝐝𝐮𝐬𝐭𝐫𝐲 𝐋𝐞𝐚𝐝𝐞𝐫𝐬⭐️ “Abdul helped us rethink our lead gen with AI-powered decision-making. His work with LLMs and pipelines was key.” — HS, Director of Data & ML, EZ Pack “Game-changer. Abdul brought serious AI expertise that moved the needle fast.” — Thomas E., CEO, Mission BI —------------------------------------------------------------------- 𝐂𝐨𝐫𝐞 𝐒𝐞𝐫𝐯𝐢𝐜𝐞𝐬 & 𝐄𝐱𝐩𝐞𝐫𝐭𝐢𝐬𝐞 ➡️ 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈 & 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐀𝐠𝐞𝐧𝐭𝐬 Autonomous LLM agents, domain-tuned business assistants, task automation, human-like conversational interfaces (OpenAI, Claude, open-source models) ➡️ 𝐑𝐀𝐆 (𝐑𝐞𝐭𝐫𝐢𝐞𝐯𝐚𝐥-𝐀𝐮𝐠𝐦𝐞𝐧𝐭𝐞𝐝 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐨𝐧) Hybrid semantic search + generation, document & knowledge-base Q&A, contextual accuracy tuning, vector-store architecture ➡️ 𝐋𝐋𝐌 𝐅𝐢𝐧𝐞-𝐓𝐮𝐧𝐢𝐧𝐠 & 𝐄𝐯𝐚𝐥𝐮𝐚𝐭𝐢𝐨𝐧 Domain-specific fine-tuning (QLoRA), benchmark evaluation (perplexity, BLEU, custom QA metrics), reliability & guardrail testing ➡️ 𝐀𝐈 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 Python-based workflow automation, process orchestration, manual-work reduction, API & systems integration, n8n, make. ➡️ 𝐀𝐈-𝐏𝐨𝐰𝐞𝐫𝐞𝐝 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 Multi-agent data analysis, auto-generated dashboards & reports, structured + unstructured data pipelines, decision recommendations ➡️ 𝐂𝐥𝐨𝐮𝐝-𝐑𝐞𝐚𝐝𝐲 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 Production-scale deployment on AWS (Bedrock, SageMaker), GCP (Vertex AI), Azure, and Databricks —------------------------------------------------------------------- 💰 𝐊𝐞𝐲 𝐀𝐜𝐡𝐢𝐞𝐯𝐞𝐦𝐞𝐧𝐭𝐬 -Helped clients raise $3M+ through AI-powered growth. -Built 50+ AI systems, from multi-agent tools to insight engines. -Drove a 17% revenue increase in 7 months for a US startup. -Impacted 300,000+ users through data-led product strategies. -Graduated in the Top 5% in my Master’s degree class (specialization in AI) —------------------------------------------------------------------- 🛠️ 𝐓𝐞𝐜𝐡 𝐒𝐭𝐚𝐜𝐤 LLMs & Agents: GPT-4, Claude, LLaMA, Mistral, LangChain, LlamaIndex, MemGPT RAG Stack: FAISS, ChromaDB, Pinecone, Weaviate LLM Ops: Fine-tuning, Prompt Engineering, Evaluation Metrics, Guardrails Dev & Infra: Python, FastAPI, LangGraph, Streamlit, Chainlit, Flask Data Pipelines: PySpark, SQL, Event-Driven Workflows, Cloud Functions Cloud Platforms: AWS, GCP, Azure, Bedrock, SageMaker, Vertex AI, Databricks —------------------------------------------------------------------- I am available to understand your project needs and deliver the best solution efficiently. Click on the “Message” button and let’s have a chat —------------------------------------------------------------------- Keywords associated with my skill set: AI Agent Developer, AI Consultant, Chatbot Developer, AI Automation Expert, AI Integration Specialist, Machine Learning Engineer, LLM Developer, Generative AI, Agentic AI, Multi-Agent Systems, Large Language Models (LLMs), GPT-4, Claude, LLaMA, Mistral, LangChain, LlamaIndex, LangGraph, Retrieval-Augmented Generation (RAG), Semantic Search, Knowledge Retrieval, Vector Databases, FAISS, ChromaDB, Pinecone, Weaviate, Custom Embeddings, Memory Layers, Prompt Engineering, LLM Fine-Tuning, LLM Evaluation, MLOps, Model Deployment, AI Data Analysis, NLP, Python, FastAPI, Chainlit, Data Pipelines, PySpark, SQL, AWS, GCP, Azure, Bedrock, Vertex AI, SageMaker, Databricks, Cloud Functions, API Integration, Open Source Models, Healthcare AI Engineer, Healthtech, Edutech, Fintech.