Phase 2 Core Sync Engine

@ZohaibRoy

⭐⭐⭐⭐⭐ Build a Powerful Synchronization Engine for Your Data Needs ❇️ Hi My Friend, I hope you are doing well. I've reviewed your project requirements and see you are looking for a solution to develop a synchronization engine. You don't need to look any further; Zohaib is here to help you! My team has completed 50+ similar projects related to automation and data integration. I will create a robust system to eliminate manual syncing, streamline workflows, and implement a self-monitoring automation pipeline, all within your budget. ➡️ Why Me? I can easily build your synchronization engine as I have 5 years of experience in Python development, API integration, and cloud deployment. My skills cover advanced Python scripting, middleware development, and working with various APIs. Additionally, I have a strong grip on Docker, AWS, and PostgreSQL, ensuring a comprehensive approach to your project. ➡️ Let's have a quick chat to discuss your project in detail and let me show you my previous work. Looking forward to discussing this with you in our chat. ➡️ Skills & Experience: ✅ Advanced Python Development ✅ API Integration ✅ Middleware Development ✅ Docker Deployment ✅ AWS (ECS, Lambda) ✅ PostgreSQL ✅ SQL Database Integration ✅ Error Handling ✅ Automation Logic ✅ Event-Driven Architecture ✅ Cloud Automation ✅ Conditional Workflows Waiting for your response! Best Regards, Zohaib

@kamran2012

Good to see this project, I will build the bidirectional sync engine connecting Salesforce, NetSuite, Google Workspace, and PostgreSQL, with event driven routing, retry logic with backoff, and dead letter queues all containerized for AWS ECS. On a similar multi system pipeline, moving from polled syncs to webhook driven triggers cut sync latency and eliminated most duplicate record issues. I will wire yours the same way. Questions: 1) For the Salesforce/NetSuite connectors, are the RESTlet scripts on the NetSuite side already deployed from Phase 1, or will I be writing those as well? 2) What is the expected peak transaction volume per hour across all systems? Share the Phase 1 repo and current API credentials setup, and I will map the data flow diagram before writing any code. Ready to start whenever you are. Kamran

@vishal1145

Your sync engine will fail under load if you're polling APIs instead of using event-driven webhooks. Salesforce and NetSuite both throttle aggressively — without proper queue management and exponential backoff, you'll hit rate limits during bulk operations and create data inconsistencies. Quick questions - are you planning to handle conflict resolution when the same record updates in multiple systems simultaneously? And what's your target sync latency for high-priority transactions? Here is the architectural approach: - PYTHON: Build idempotent sync handlers with retry decorators and circuit breakers to prevent cascading failures across your pipeline. - AWS LAMBDA + SQS: Deploy event-driven workers that process webhook payloads asynchronously, decoupling API calls from business logic execution. - POSTGRESQL: Design an audit schema with JSONB columns for flexible payload storage and indexed timestamp queries for compliance reporting. I've built similar multi-system sync engines for 2 SaaS platforms processing 500K+ transactions daily without data loss. Let's schedule a 20-minute architecture review to validate your conflict resolution strategy before you start coding.

@toriquldev123

Hello There! I’m Md. Toriqul Islam, and I’m excited to partner with you. I can dive into your project immediately. I’m a full stack developer with over 10 years of experience in Python, enterprise integrations, AWS, Docker, and workflow automation. I understand Phase 2 focuses on building a robust synchronization engine with bidirectional data flows between Salesforce, NetSuite, Google Workspace, and PostgreSQL. The solution will include secure API integrations, event driven automation, audit logging, resilient retry mechanisms, and scalable deployment on AWS ECS. I have delivered similar enterprise integration and automation projects. I am skilled in Python, Salesforce API, NetSuite API, PostgreSQL, Docker, AWS ECS, Lambda, SQS, REST APIs, OAuth, and middleware development. I’m ready to start immediately and would be happy to discuss the Phase 2 implementation plan. Feel free to share the existing architecture and roadmap. Looking forward to hearing from you. Best regards, Md. Toriqul Islam

@rosscarter1011

Hey, since Phase 2 is really about that Salesforce-NetSuite-Postgres triangle syncing cleanly, I’d build it around a queue-based middleware layer so retries and dead-letter handling don’t turn into a mess later. NetSuite’s SuiteTalk rate limits usually trip people up on bidirectional syncs, so I plan for backoff from day one instead of bolting it on after. Containerizing for ECS with proper health checks keeps it self-monitoring like you want. Are approval workflows triggered from Salesforce, NetSuite, or both sides?

@alizain721

The real risk for Phase 2 is not building connectors — it is getting bidirectional conflict resolution, idempotency, and conditional routing wrong so your automations create more manual cleanup than they remove. I’ve handled the same class of problem before with a rules-based transaction engine that reconciled bank feeds against user-entered data and applied multi-step business rules without mistakes. My practical approach: deliver an event-driven core sync engine that treats each external system as a bounded participant and keeps a single source of truth in PostgreSQL. Key pieces I will implement first and in priority order: - Reliable connectors for Salesforce REST and NetSuite SuiteTalk/RESTlets, plus a Google Workspace connector for user and calendar sync. - An event bus using SQS for guaranteed delivery, with worker services in Docker (ECS) for heavy processing and Lambda for lightweight transforms. - Transaction state and full audit logging in PostgreSQL, with idempotency keys, versioned object mapping, conflict resolution policies, automated retries with exponential backoff, and dead-letter queues for manual review. - Observability and self-healing: CloudWatch metrics, structured logs, health endpoints, and automated alerts so the pipeline is self-monitoring. Relevant project: Tax Plan Hero — I built a rules-based sync and strategy engine that ingested external feeds, applied conditional logic, and produced audited outputs stored in PostgreSQL. That experience maps directly to building multi-step, admin-configurable routing and reconciliation for sales, finance, and user data. Technical summary and assumptions: - Proposed bid: $500 - Stack: Python, Docker, AWS ECS + SQS + Lambda, PostgreSQL, Salesforce REST, NetSuite SuiteTalk/RESTlets, OAuth - Estimate: 3–6 weeks for MVP core engine (assumes available sandbox credentials and documented object mappings) Do you have Salesforce and NetSuite sandbox credentials and an existing data mapping or reconciliation rules document I can review? If so, I’ll prepare an initial connector plan and test harness within 72 hours.

@vladang

It sounds like Phase 2 is where the integration stops being about connecting APIs and starts becoming about keeping several business systems reliably in sync without people stepping in when something goes wrong. That's where I'd focus first on the synchronization rules and transaction flow before writing the middleware itself. Once those paths are clear, I'd build the Python services around idempotent processing, secure OAuth authentication, webhook handling where available, and reliable polling where it isn't. Every sync would be traceable in PostgreSQL so failures can be replayed instead of guessed, with retries, exponential backoff, and dead-letter queues preventing bad records from blocking the pipeline. I worked on a similar backend integration project at Aras using Python and PHP, where reliable synchronization and auditability mattered more than raw throughput, and that experience carries over well here. One thing I'd like to clarify is whether Salesforce or NetSuite should be treated as the source of truth when conflicting updates occur. I'm ready to get started.

@iimtpradeepdash

Multi-way sync at this level lives or dies on two things: atomic event handling and mapping edge cases across the different APIs. You need idempotent triggers so no data gets duplicated or lost on retries, especially between Salesforce and NetSuite. I built a sync engine between Salesforce, ERP, and GSuite for a logistics AI platform (PackSmart AI), with Python services wrapped in Docker and deployed on AWS ECS—full audit logging, auto-recover from partial failures, and dead-letter queue processing. Stack: Python 3, async/requests for APIs, custom middleware layer, PostgreSQL for transactional state and audit, containerized with Docker Compose and deployed to ECS. Advanced exception handling and retry logic are standard. Has your NetSuite instance already exposed SuiteTalk endpoints, or will I need to build that init as part of the first run? Available to start this week. Pradeep

@godesignpk

Hi, I've gone through your requirements for the Phase 2 Core Sync Engine and I'm confident we can build a robust, event-driven automation pipeline to handle your complex data flows. We specialize in developing custom middleware and secure API connectors, integrating systems like Salesforce, NetSuite, and PostgreSQL, and deploying scalable solutions on AWS using Docker and Lambda. Our focus will be on creating a high-performance, self-monitoring engine that eliminates manual syncing and streamlines your approval workflows, ensuring complete audit trails and resilient error handling. We're rated 4.88★ across 905 client reviews. Alacua L. from Argentina said: 'They are great, very professional, very responsive.' Could you share more about your specific timeline expectations for this phase?

@techsty2014

Hi there, We will build the core sync engine: bidirectional connectors for Salesforce, NetSuite, Google Workspace, and PostgreSQL, packaged in Docker for AWS ECS. For resiliency, we will wire SQS as the dead-letter queue with exponential backoff retries. Each transaction gets a state row in PostgreSQL so the audit trail is complete and every failure is recoverable without manual intervention. A couple of quick things to confirm: 1) Are the Salesforce and NetSuite API credentials and sandbox environments ready for Phase 2? 2) Should the sync engine run on a schedule, pure event-driven webhooks, or a hybrid of both? The number quoted here is a starting estimate. The exact cost and timeline will be confirmed after we go through the full scope together. Send me a message and we can go over the details. Best regards, Faizan

@MIndlabsAi6

Hey there! I'm really pumped about this opportunity! I recently led a project with similar challenges and nailed it. Drawing from my experience in Python, Amazon Web Services, Hadoop, PostgreSQL, Elasticsearch, OAuth, Docker, AWS Lambda, I’m ready to dive into your project. Please come over chat and discuss your requirement in a detailed way. Cheers, Vishal Maharaj

@SkillCrafts

Your Phase 2 Core Sync Engine proposal aligns perfectly with my experience building high-throughput, event-driven data pipelines. I recently developed a similar integration layer for a SaaS platform, synchronizing customer data between HubSpot, Stripe, and a custom data warehouse, achieving a 99.9% data integrity rate and reducing manual reconciliation time by over 80%. I understand the critical need for a robust, self-monitoring system that can handle complex business logic and bidirectional flows across disparate systems like Salesforce, NetSuite, and Google Workspace. My approach will leverage Python as the core development language, utilizing libraries like `SQLAlchemy` for efficient PostgreSQL interaction and `requests` for robust API integrations with Salesforce, NetSuite, and Google Workspace. I'll implement an event-driven architecture, likely using a message queue system (e.g., RabbitMQ or Kafka, depending on infrastructure preferences) to decouple services and ensure resilience. For complex business logic, I’ll design modular, testable functions and classes, prioritizing clear data transformation and validation steps. The pipeline will be designed for scalability, with asynchronous processing where applicable, and incorporate comprehensive logging and monitoring for self-healing capabilities. To ensure we're perfectly aligned from the outset, could you clarify the preferred methodology for handling API rate limits and error retries across the integrated platforms? Additionally, what are the primary performance metrics or SLAs you envision for this core sync engine? I’m eager to discuss how my expertise can deliver a high-performance, reliable solution for your Phase 2 objectives.

@mobasherreza10

With my extensive expertise, especially in Python scripting, middleware development, and Docker deployment such as Amazon Web Services (AWS) and AWS Lambda, I'm well-equipped to help steer your project in the right direction! For this role that requires a crafting a robust synchronization engine for Salesforce, NetSuite, Google Workspace, and PostgreSQL database, I have substantial proficiency in the required technical skills. I pride myself on my ability to build highly scalable Python scripts with complex conditional routing and advanced exception handling not feasible through regular automated tools. Additionally, my mastery over Salesforce REST APIs, NetSuite SuiteTalk/RESTlets integration combined with PostgreSQL backed database would ensure efficient multi-system integration fostering seamless data flows.

@Web1devloper

With an extensive background in Data Analytics and Science, I bring a unique understanding of the importance of efficient data syncing and management. My skills with Python, Amazon Web Services, Docker, and PostgreSQL make me the perfect fit for this project. I’ve created powerful automated scripts capable of handling complex conditional routing and multi-step business logic - which aligns perfectly with your needs. Having worked with large datasets in various industries over my 8-year career, I’ve gained valuable experience in system integration and API development. Salesforce API, NetSuite API, Webhooks, OAuth, or REST APIs; these are tools I'm comfortable using to create secure API connectors. I'm also well-versed in using Docker for cloud deployment on AWS ECS to ensure scalability and high-availability – both vital requirements for this project. Furthermore, my expertise goes beyond just developing the synchronization engine. My work extends to ensuring robust error handling methodologies and maintaining complete compliance logs. I aim for a self-healing pipeline that brings much needed resilience to your data systems. In essence, my skillset is designed to help you achieve your goals of eliminating manual syncing, automating workflows seamlessly while streamlining approval processes. Together, we can build a pipeline that not only meets but exceeds your expectations. Let's get started on creating a high-performance data workflow engine!

@revival786

Greetings! I will build the core synchronization engine with Python for bidirectional data flows between Salesforce, NetSuite, Google Workspace, and PostgreSQL. I will develop middleware, API connectors, Docker containers for AWS ECS, and implement error handling with retry logic. I have multi system integration and automation experience. Send your API credentials and workflow requirements. Thanks, Revival

@engruhulajom

Hello There! I’m Ruhul Ajom, and I’m excited to partner with you. I can start immediately. I’m a full-stack developer with 10+ years of experience building enterprise automation systems, Python middleware, and cloud-native integrations. I understand Phase 2 focuses on developing a scalable synchronization engine with bidirectional data flow between Salesforce, NetSuite, Google Workspace, and PostgreSQL. I have experience building Python-based integration platforms with secure APIs, Docker, AWS ECS, event-driven workflows, retry mechanisms, audit logging, and resilient automation pipelines. I have rich experience in Python, Salesforce API, NetSuite API, PostgreSQL, Docker, AWS ECS, Lambda, SQS, REST APIs, and workflow automation. I’m ready to start immediately and would be happy to discuss the architecture, deployment strategy, and implementation timeline. Looking forward to hearing from you. Best regards, Ruhul Ajom

@securetechs

Hi, just wrapped up a bidirectional sync service between PostgreSQL and Elasticsearch last month, same core problem of keeping both sides consistent without duplicate writes or lost updates during conflicts. For your Phase 2 engine I'd start by mapping your data model and defining a conflict-resolution strategy (timestamp/version based) so we don't overwrite live records. Then build the sync workers as Python services on AWS Lambda, using OAuth for the source/target auth and Docker to containerize everything for consistent deploys. I'll queue changes through a durable log so retries don't create duplicates, then load-test with concurrent writes on both ends before cutover, and hand you a staging environment plus logs showing sync latency and conflict counts. Realistic timeline is 5-7 days given the moving parts across two data stores plus Lambda orchestration. Is Phase 1 already deployed, and do you have schema/API docs for both source and target systems ready, or should I start by reverse-engineering the current setup? Regards, Imtiaz, SecureTechs

@Ritesh11gupta

Building a core synchronization engine sounds like an exciting challenge! With my skills in Python and PostgreSQL, I can help streamline this process. What specific features are you hoping to prioritize in this phase?

@goranm16

Hello, the "Phase 2" framing tells me you already know exactly where no-code tools break down, and that is precisely the kind of sync engine I build. I have delivered Python middleware connecting Salesforce REST APIs with ERP systems and PostgreSQL backends, handling OAuth token refresh, conditional routing, and multi-step approval logic in production. My pipelines run as Docker containers on AWS ECS with SQS-backed retry queues, exponential backoff, and dead-letter handling, so failures recover on their own instead of paging anyone at 3am. Every transaction state and sync status gets written to Postgres for a full audit trail. NetSuite SuiteTalk and RESTlets are familiar territory from prior ERP integration work. I am in CET, work with clean repos, tested code, and clear documentation, and can walk you through my architecture approach before we start. Best regards, Goran