Hire the Best Apache Spark Specialists

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.

I specialize into integrating CRM APIs into data dashboards and AIs for insight generation. Technical Skills: - Python (API integration, cleaning, transformation), Go, SQL, Databricks, PySpark - Airflow, Dagster, Prefect, Fivetran - Power BI, Tableau, Looker - AWS: Batch, Step Functions, Glue, Athena, Lambda, S3, EC2, IAM, KMS, SQS, Boto3 - GCP: Cloud Run, GKE, Compute Engine, Dataproc, BigQuery, GCS, Pub/Sub - Docker, Kubernetes, Terraform, GitHub Actions - Snowflake, Bigquery, Databricks

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, 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!

✅ 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.

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

Hi, I’m Anita, managing this Upwork account. Our projects are led by Pankaj, a Principal Data Engineer with 19+ years of experience, supported by a team of skilled data engineers, cloud specialists, and analytics professionals. Together, we deliver end-to-end data engineering and analytics solutions — from design to deployment and training. Most of our experience lies in the banking, finance, and e-commerce domains, where we have built and optimized large-scale data platforms for risk management, fraud detection, customer analytics, and regulatory reporting — ensuring performance, scalability, and reliability. 🔹 Key Expertise Big Data & Spark: 10+ years of experience with PySpark, Spark SQL, Spark Scala, and Structured Streaming for large-scale and streaming data pipelines. Programming Languages: Proficient in Python and Scala for ETL, automation, and distributed data processing. Cloud & Platforms: Expertise across AWS (S3, Glue, EMR, Redshift, Kinesis), Azure (Data Factory, Synapse, Databricks), and GCP (BigQuery, Dataflow, Pub/Sub). Modern Data Stack: Hands-on with dbt, Snowflake, and Apache Airflow for ELT, orchestration, and data modeling. Domain Knowledge: Strong experience in banking data engineering, plus e-commerce analytics, recommendation engines, and customer insights. Team Capabilities: Our team can handle complete data projects — including architecture setup, pipeline development, performance tuning, and dashboard delivery. Training & Mentorship: We also provide corporate and individual training in Python, PySpark, and modern data engineering, using real-world projects like: “Designing a Kafka → PySpark → Snowflake → dbt → Airflow data pipeline.” We combine deep technical expertise, agile delivery, and strong business understanding to deliver scalable, cloud-native, and future-ready data platforms tailored to your goals. Let’s connect to discuss how our team can help you design, build, and deliver robust, modern data engineering solutions for your business. — Anita (Account Manager) & Pankaj (Principal Data Engineer & Delivery Lead)