Hire the Best MapReduce Specialists in Mumbai, IN

I am a senior Data Engineer with 6+ years of experience designing and building large-scale data pipelines and analytics platforms across finance, consulting, and enterprise domains. Currently working as a Sales Data Analytics Engineer at Russell Investments, I design and maintain high-performance data pipelines processing millions of records daily using Python, Pandas, Polars, Spark, and Snowflake. I have strong experience in building end-to-end ETL/ELT systems, optimizing SQL for sub-second query performance, and automating workflows using Apache Airflow and CI/CD. Previously at Cognizant, I built real-time and batch data platforms using Kafka, AWS Glue, S3, Snowflake, and Vertica, handling 10M+ records daily and achieving 99.9% pipeline reliability. I specialize in data modeling, performance tuning, cost optimization, and building production-grade analytics systems. Core expertise: • Data Warehousing: Snowflake, Vertica, SQL Server • ETL & Orchestration: Airflow, AWS Glue, Control-M • Big Data: Spark, Kafka, PySpark • Programming: Python, SQL (Advanced), Pandas, Polars, NumPy • Cloud: AWS (S3, Redshift, Glue), CI/CD, Git • Data Modeling & Optimization What clients get when working with me: ✔ Scalable, reliable data pipelines ✔ Optimized Snowflake & SQL performance ✔ Clean, production-ready Python code ✔ Automated workflows with monitoring ✔ Clear communication and on-time delivery I help startups and enterprises with: End-to-end data pipeline development Snowflake & cloud data warehouse design SQL performance tuning Real-time & batch ETL systems Data migration & modernization Analytics-ready data models

I’m a Data Engineering Professional with 4+ years of experience delivering innovative, scalable, and efficient solutions for complex data challenges. My expertise spans Big Data, Data Warehousing, Cloud Computing, and Data Analytics, ensuring seamless ETL pipelines and actionable insights for clients worldwide. 🌟 My Mission: To help businesses leverage data for smarter decisions, optimized workflows, and measurable results. 🛠️ Core Competencies 📊 Big Data & Data Engineering Proficient in Apache Spark, Hadoop, MapReduce, Hive, Kafka, Airflow, and Snowflake. Real-time and batch data processing expertise using Spark Streaming and Flink. Skilled in tools like Presto, Cloudera Manager, StreamSets, and Zookeeper. ☁️ Cloud Platforms AWS: EC2, S3, RDS, EMR, Redshift, Lambda, Glue, Kinesis, Athena. Azure: Azure Databricks, Synapse Analytics, Data Factory, Data Lake. GCP: BigQuery, Dataflow, and other scalable services. 📈 Data Visualization & Business Intelligence Expertise in crafting dashboards with Tableau, Power BI, and Grafana for actionable insights. 💾 Databases Mastery of SQL and NoSQL databases, including SQL Server, PostgreSQL, MongoDB, Cassandra, and HBase. 💻 Programming & DevOps Advanced coding skills in Python, Scala, and Java for ETL workflows and automation. Experience with Docker, Kubernetes, and other DevOps tools for smooth deployment. 🌟 Why Choose Me? ✅ Proven Track Record Successfully designed and implemented end-to-end pipelines, processing massive datasets with exceptional performance. ✅ Cloud Expertise Extensive hands-on experience with AWS, Azure, and GCP, ensuring cost-effective and scalable solutions. ✅ Business-Driven Solutions Focused on aligning technical implementations with your business goals to maximize value. ✅ On-Time Delivery Reliability and adherence to deadlines without compromising quality. 💼 Let’s Collaborate! Looking for a dedicated, detail-oriented, and highly skilled Data Engineer to transform your data strategies? Let’s connect and build your next data-driven success together! 📬 Contact Me Today to discuss how I can add value to your projects.

🚀 Data Engineer & Solution Architect | Scaling Data Platforms 10× Without Breaking Them I design data systems that don’t just run, they scale, perform, and stay reliable under real-world pressure. With 7+ years building enterprise-grade platforms, I’ve seen the same story repeat: A pipeline works at 10M records… then collapses at 100M. Costs spiral. Latency explodes. Nobody wants to touch the legacy system. That’s where I come in. 🧠 What I Actually Deliver I architect cloud-native data platforms built for tomorrow not quick fixes for today. ✔ Migrate fragile legacy systems to modern, resilient architectures ✔ Design scalable data lakes and lakehouses ✔ Optimize pipelines bleeding money and compute ✔ Build real-time analytics for mission-critical decisions ✔ Create foundations ready for AI/ML workloads Result: Systems that grow with your business instead of holding it back. ⚙️ Deep Technical Expertise Across the Stack ☁️ Cloud Platforms AWS: Glue, EMR, Redshift, Kinesis, S3, Lambda, Lake Formation, DMS, MSK, RDS Azure: Data Factory, Synapse, Databricks, DevOps GCP: Dataflow, Cloud Functions, Cloud Storage 🔥 Big Data & Streaming Apache Spark (Scala & PySpark) • Kafka • Kinesis • NiFi • Hadoop Ecosystem • Airflow • Delta Lake 💻 Programming Python • Scala • SQL • Shell • Java 🗄️ Databases & Storage PostgreSQL • MySQL • Oracle • SQL Server • MongoDB • Cassandra • DynamoDB • Elasticsearch 🛠️ DevOps & Infrastructure Docker • Kubernetes • OpenShift • Terraform • Jenkins • Ansible • Git 📊 Observability & Governance CloudWatch • ELK • Grafana • Athena IAM • Lake Formation • Encryption • Audit Logging • Okta • Cognito 🏢 Enterprise Experience That Matters I’ve delivered production systems for Fortune 500 organizations across finance, energy, hospitality, and SaaS handling hundreds of millions of records daily. From ingestion → transformation → real-time analytics → security → DevOps automation — I design the full lifecycle. 🏆 Proven Impact ✔ Re-architected legacy pipelines → 5× performance boost & 60% cost reduction ✔ Built event-driven systems processing 500M+ records/day ✔ Delivered secure data lakes with row-level governance ✔ Reduced MTTR by 70% with end-to-end observability ✔ Led zero-downtime cloud migrations ✔ Secured $2B+ transaction data with encryption platforms 🤝 Best Fit For Organizations That Need 🔹 Cloud migration with strong architectural guidance 🔹 Performance or scalability bottlenecks 🔹 Data platforms for AI/ML initiatives 🔹 Multi-cloud or hybrid strategies 🔹 Long-term reliability over quick hacks ⚠️ Not a Fit For ❌ One-off scripts or basic SQL tasks ❌ Temporary data cleanup work ❌ Short-term patch solutions I focus where architecture decisions create lasting business value. 💬 What Clients Value Most Clear thinking on complex problems Communication executives understand Engineering teams trust Systems built to last 👉 If your data platform needs to scale, stabilize, or modernize then let’s talk.

 Highly Skilled IT Professional Experience in GCP and Azure Cloud with over 7+ years of experience working as GCP and Azure Data Engineer.  Overall, 16+ years in IT Experience. In Software Design, Development, Analysis, Testing, Data Warehouse and Business Intelligence tools.  Working within an Agile delivery methodology production implementation in iterative sprints GCP : BigQuery – Created external table on GCS Parque files, Views with Dedupe logic, Wrote the dynamic batch script to find the current/invalid parquet files in GCS 🖎 DataProc – Written in PySpark / Spark SQL program to transform data and used dataproc cluster to run the job. Implemented Delta lake 🖎 Composer, Apache Airflow – Used for workflow orchestrations. 🖎 Git – Used to maintain as a code repository 🖎 GCS – Storage used to keep processed data. Parquet/CSV files used to store data. 🖎 Programming – PySpark, Python, and Spark SQL used for script Cloud Data Platform (Azure):  Implemented standard Databricks Notebook used to load Full load and Delta load (Type 1) to process a large volume of data with all the business rules and transformation.  Used Scala and Spark SQL language to create standard Databricks Notebook  Implemented Azure Key Vault service to store all the vital credentials like Service Principal key, Database credentials, Storage connection string, and others  Knowledge of ADLA (U-SQL) replacement with Azure Databricks for data processing  Designed and implemented highly performant data ingestion ADF pipelines from multiple sources using Azure Databricks  Created some UDF for logging, History load from multiple date folders from data lake storage DW& Data Modeling:  Experience in OLTP/OLAP System Study, developing Database Schemas like Star Schema and Snowflake Schema used in relational, dimensional, and multidimensional modeling.  Experience in analysis, design, and construction of Data warehouses.  Expert Experience in Normalization, De-normalization.  Implemented Slowly Changing Dimensions - Type I & II in Dimension tables as per the requirements ETL:  Proficient in using SQL Server Integration Services to build Data Integration and Workflow Solutions, Extract, Transform and Load (ETL) solutions for Data warehousing applications.  Skilled in Business Intelligence tools like SQL Server 2008R2 Integration Services (SSIS).  Experience creating SSIS packages to automate the Import and Export of data to and from SQL Server 2008 using SSIS tools like Import and Export Wizard, Package Installation, and BIDS. T-SQL:  Extensive experience in using T-SQL (DML, DDL) in SQL Server 2012 / 2000 platforms.  Experienced in creating Tables, Stored Procedures, Views, Indexes, Cursors, Triggers, User Profiles, User Defined Functions, Relational Database Models, and Data Integrity in observing Business Rules.  Implemented Change Tracking (CT) and Change Data Capture (CDC) functionality  Extensive knowledge in tuning T-SQL, Query Optimization to improve the Stored Procedures/Functions performance and availability.

Senior Data Engineer | AWS · Snowflake · Spark · Kafka | 8+ Yrs I build data pipelines that are fast, reliable, and easy on your cloud bill. Currently AVP of Data Engineering at a leading Indian financial services firm, where I lead a team of six and own projects end-to-end — architecture to production. What I can help with: • ETL/ELT pipelines (AWS Glue, Airflow, Spark, Python) • Snowflake setup, performance tuning & cost reduction • Real-time streaming with Kafka • Cloud migrations (on-prem → AWS) • Data governance, CI/CD & automation I start with your business problem, not the tech stack — and I respond fast. Let’s talk.

🔹 I build data platforms that handle petabytes of data, millions of events, and ensure zero-tolerance downtime. I’m a senior data engineer and cloud architect with over a decade of experience building production-grade, petabyte-scale data platforms for high-growth, data-intensive businesses. I specialize in real-time analytics, low-latency systems, and cloud cost optimization — the kind of work that breaks if done wrong and gets noticed by leadership when done right. 🚀 Proven Business Impact - +18% revenue uplift by detecting and blocking high-risk fraud users in a real-time data platform - Less than 30ms read/write latency for high-DAU applications handling millions of events per day - Production-grade pipelines supporting analytics & ML with strict data quality guarantees What I’m Typically Brought In For - Stabilizing broken or unreliable data pipelines - Designing real-time or near-real-time architectures - Reducing Snowflake/cloud warehouse costs Core Stack: - Cloud & Warehousing: AWS, GCP, Snowflake, Databricks - Data Engineering: Spark, Kafka, Airflow, dbt, Terraform - Real-Time Systems: Kafka, Flink, DynamoDB - Architectures: Data Lakes, Warehouses, Lakehouses How I Work I ship systems that survive production, scale, and audits. That means clear scope, measurable outcomes, and no “hope it works” engineering. 📌 If your data platform is a bottleneck or a liability, let’s fix it properly. Message me to discuss your system and constraints.