Freelancers using AWS in PunjabFreelancers using AWS in Punjab
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Abubakar Chan's avatar
Abubakar Chan
proLahore, Pakistan
AI Automation Engineer | Full-Stack Apps & Integrations
66x
Hired
4.9
Rating
155
Followers
ANYTHING_EXPERT

Expert

REPLIT_EXPERT

Expert

+2
AI Automation Engineer | Full-Stack Apps & Integrations
Cover image for Provider Portal for Healthcare MSO
Provider Portal for Healthcare MSO
4
46
Cover image for Gut Health SaaS Platform Development
Gut Health SaaS Platform Development
1
17
Cover image for Magnai | UK Public Affairs
Magnai | UK Public Affairs
6
88
Cover image for Humoni - secure housing in under 72 hours
Humoni - secure housing in under 72 hours
7
146
AWS(1)
Umar Abdullah's avatar
Umar Abdullah
maxLahore, Pakistan
Full-Stack Dev (Web, Mobile, Desktop) & Chromium Browser Dev
8x
Hired
5.0
Rating
159
Followers
Full-Stack Dev (Web, Mobile, Desktop) & Chromium Browser Dev
Cover image for Chrome Extension Development for school's student Monitoring
Chrome Extension Development for school's student Monitoring
1
14
Cover image for Full-Stack Developer | Chromium Expert | Chrome Extension
Full-Stack Developer | Chromium Expert | Chrome Extension
7
83
Cover image for Chromium Browser Development for enterprise
Chromium Browser Development for enterprise
7
66
Cover image for Real Estate Authority Modern Website Development
Real Estate Authority Modern Website Development
1
34
AWS(1)
Advancing Data Solutions's avatar
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 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.
0
163
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
0
209
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.
0
205
Cover image for Batch ETL Data Warehouse Modernization Led
Batch ETL Data Warehouse Modernization Led modernization of a legacy batch ETL pipeline into a scalable AWS-based data warehouse. Replaced manual SQL jobs with an automated system loading diverse sources into Amazon Redshift. Ingestion: Daily CSVs and API data land in S3; S3 events trigger Lambda to launch Glue Crawlers and update the Data Catalog. Transformation: Glue PySpark jobs join and cleanse sales, inventory, and customer data, apply quality checks, and move errors to a quarantine path. Output: Partitioned Parquet files stored in S3 for loading into Redshift.
0
177
AWS(4)
Adil Shahzad's avatar
Adil Shahzad
proLahore, Pakistan
Senior DevOps & DevSecOps Engineer · Cloud Security
Senior DevOps & DevSecOps Engineer · Cloud Security
Cover image for Secure Kubernetes platform for a
Secure Kubernetes platform for a regulated environment Production Kubernetes for regulated finance, with scanning enforced in every pipeline before anything deploys. Who it was for: A regulated financial services environment. The problem. Production Kubernetes in regulated finance has to satisfy two audiences at once: engineers who need to ship, and auditors who need to see that nothing ships unchecked. What I did. Provisioned clusters and supporting networking with Terraform so the platform is reproducible and reviewable. Designed the routing layer through a gateway and ingress controllers. Built reusable pipeline workflows with image, IaC and policy scanning embedded, so the security step isn't something a team can skip under deadline — it is the path to production. The result. Every build is scanned before deploy, and control evidence is a by-product of the pipeline rather than a separate exercise.
0
32
Cover image for Click-ops to Terraform on live
Click-ops to Terraform on live production An entire running cloud estate brought under infrastructure as code without taking production down. Who it was for: An organisation whose cloud estate had grown by hand over several years. The problem. Everything had been built through the console. Nothing was reproducible, nothing was reviewable, and nobody could say with confidence what would happen if a region went away. Rebuilding from scratch wasn't an option — the estate was live. What I did. Imported existing resources into state rather than recreating them, working through the dependencies that don't import cleanly by hand. Refactored into modules along the way so the output stayed maintainable. Every change went through plan review before apply. The result. The full estate is under version control with reviewable changes, and the cutover ran with zero production downtime.
0
32
Cover image for FinOps automation across seven environments Automated
FinOps automation across seven environments Automated scheduling and rightsizing that took roughly $280k a year out of the cloud bill. Who it was for: A large regional bank running seven cloud environments. The problem. Seven environments, most of them idle outside working hours, and no visibility into which team was spending what. Cost conversations were happening after the invoice rather than before. What I did. Established a cost baseline per environment, then automated resource scheduling so non-production stopped paying for nights and weekends. Rightsized the workloads that were provisioned for peaks that never came. Built daily and weekly cost reporting so stakeholders could see the trend without asking for it. The result. Around $280k of annual run-rate removed, with ongoing reporting that keeps the saving from creeping back.
0
63
Cover image for Driving SAMA CSF maturity from Level 2 to Level 3
Driving SAMA CSF maturity from Level 2 to Level 3
0
1
AWS(3)
Saim Sheikh's avatar
Saim Sheikh
Rawalpindi, Pakistan
I build AI-powered apps & automation that run themselves.
I build AI-powered apps & automation that run themselves.
Cover image for Your social media manager called
Your social media manager called in sick. Our AI pipeline didn't. Every morning at 9 AM, this is what fires automatically at Edge of Tech: A cron job scans our git logs and recent project work for something worth saying. Cross-references trending topics in dev and AI. Picks the best angle for the day. Then Claude writes a full LinkedIn post, an X post, and a carousel — all in our brand voice. A branded image card gets generated and rendered from a JSX template. The whole package lands in our Discord with one-tap publish buttons. No scheduler. No copywriter. No "what should we post today?" conversation. If you're a business owner manually batching content on Sundays, or paying someone to post three times a week with stock images and random hashtags — that's not a content strategy. That's a recurring chore. We built this for ourselves because we had the same problem. Now we build it for clients. What the pipeline delivers: AI-generated posts calibrated to your voice, platform-specific formatting (LinkedIn reads differently to X), branded image cards with your visual identity, curated hashtags by tier, and a one-tap approval workflow in Discord. You spend five minutes a day reviewing. Everything else runs on its own. If your last three LinkedIn posts were two weeks apart, edgeof.tech (http://edgeof.tech) is worth a conversation. #AI #ProductDevelopment #AIAgents
0
28
Cover image for Discord Bots — Edge Pipelines
Discord Bots — Edge Pipelines
0
7
Cover image for Scarlet: AI-Powered Agency Toolkit Development
Scarlet: AI-Powered Agency Toolkit Development
0
9
Cover image for Dynamic Optimization of Apache Kafka Configurations
Dynamic Optimization of Apache Kafka Configurations
0
8
AWS(4)
Toolshed (Data, Automation, AI Agents, Buildship, Framer)'s avatar
Toolshed (Data, Automation, AI Agents, Buildship, Framer)
maxLahore, Pakistan
Data, Automation, AI Agents, Buildship, Framer, Bubble
$100k+
Earned
7x
Hired
5.0
Rating
74
Followers
TOP_INDEPENDENT

Top

FRAMER_EXPERT

expert

+1
Data, Automation, AI Agents, Buildship, Framer, Bubble
Cover image for Financial & Usage Analytics for YC-backed healthcare startup
Financial & Usage Analytics for YC-backed healthcare startup
1
30
Cover image for Plan Path End-User Patient Insurance Portal Development
Plan Path End-User Patient Insurance Portal Development
2
26
Cover image for Construction FP&A & Revenue AI Platform
Construction FP&A & Revenue AI Platform
6
314
Cover image for Luxury Framer Architecture Portfolio
Luxury Framer Architecture Portfolio
1
25
AWS(2)