Freelancers using AWS EMR

Freelancers using AWS EMRFreelancers using AWS EMR

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Advancing Data Solutions

proLahore, Pakistan

AI & Data Engineer|Data & AI Architect| AWS|Azure |Snowflake

AI & Data Engineer|Data & AI Architect| AWS|Azure |Snowflake

Cover image for Real-Time Analytics Platform on AWS

Real-Time Analytics Platform on AWS designed to ingest, process, and visualize high-volume streaming data from IoT devices and application logs. Ingestion: Device telemetry (IoT Core) and application logs are published into Amazon Kinesis Data Streams, followed by lightweight routing and enrichment using AWS Lambda. Processing & Storage: Amazon EMR performs heavy data transformations via Spark Structured Streaming, landing the curated output into Amazon S3 as partitioned Parquet files. AWS Glue then handles batch transformations before loading the data into Amazon Redshift for the analytics workload. Orchestration & Serving: AWS Step Functions coordinate the batch processing workflows. Finally, Amazon QuickSight generates actionable business dashboards while Amazon CloudWatch monitors operational metrics and alarms

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Cover image for Real-Time Analytics Platform on AWS

Real-Time Analytics Platform on AWS

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Cover image for Oracle to Amazon RDS PostgreSQL
Designed

Oracle to Amazon RDS PostgreSQL Designed and Implemented a secure, scalable architecture to migrate an on-prem Oracle database to Amazon RDS for PostgreSQL. Data Flow: Modeled end-to-end flow, used AWS Glue (SCT) for schema conversion and DMS for full-load and CDC. Stored artifacts in S3 and loaded into RDS. Services: Glue for conversion, DMS for Migration , S3 for artifacts, and RDS as target. Security: IAM roles with least privilege, KMS for encryption at rest. HA & DR: Architected in us-east-1 with Glue, DMS, RDS, S3, and monitoring via CloudWatch.

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Cover image for OnPrem .NET to AWS Migration

Migrated

OnPrem .NET to AWS Migration Migrated an on‐premises .NET web application and SQL Server database to AWS to achieve scalability, high availability, and cross‐region resilience. The legacy environment ran on Windows servers with a clustered SQL Server, resulting in high maintenance and limited elasticity. The new AWS architecture features EC2 Auto Scaling behind an Application Load Balancer (ALB), Amazon RDS for SQL Server with Multi‐AZ and a cross‐region read replica, and DNS failover via Route 53. ◦ Deployed the .NET application on an EC2 Auto Scaling group (Windows AMI) across private subnets in us‐east‐1. 5- Build Scalable Real-Time Data Analytics on AWS for Instant Insights Designed and implemented a real-time data analytics platform on AWS, enabling stream processing, transformation, and visualization for high-volume IoT and log data. This system was built to process and analyze millions of records per second, providing actionable insights for business decision-making. The solution leveraged AWS native services like Kinesis, Glue, Lambda, and Redshift, integrating Apache Spark Structured Streaming to handle real-time data ingestion and transformation. Airflow and Step Functions were used for workflow automation.

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Ghazi Ben Ahmed

Full-stack engineer: UI, cloud infra & data pipelines

New to Contra

Full-stack engineer: UI, cloud infra & data pipelines

Cover image for SeLoger

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Cover image for Stellantis

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Cover image for Star maps of your moment, computed from NASA data Each map i...

Star maps of your moment, computed from NASA data Each map is made for your date, time and place

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ARUN KARTHI MANI

Bengaluru, India

Crafting scalable and efficient software solutions

Crafting scalable and efficient software solutions

Cover image for Built Realtime IP blocking and Alerting System

Built Realtime IP blocking and Alerting System

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Cover image for Built Underwriting System For Users Loan Approval at scale

Built Underwriting System For Users Loan Approval at scale

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Cover image for Built Full Infra on Azure from scratch

Built Full Infra on Azure from scratch

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