AWS-Snowflake ELT Setup Support

@kashifnadeem86

Hi, I can support this setup and help turn your mapped architecture into a working AWS → Snowflake → dbt/Airflow flow. I have hands-on experience with AWS, S3, IAM, RDS, Glue/Python, DMS concepts, Snowflake stages/Snowpipe, RBAC, and workflow automation. For this budget, I’d suggest keeping the first milestone focused on a clean MVP pipeline using your sample data, then documenting how it can be extended. My approach would be: * Review your architecture diagram, RDS source, S3 layout, and sample data * Set up least-privilege IAM roles/policies for S3, Glue/DMS, and Snowflake access * Configure S3 landing/raw paths and either Glue or DMS based on the CDC requirement * Create Snowflake storage integration, external stage, file format, Snowpipe, schemas, and roles * Add a basic parameterized dbt structure and connect execution through Airflow * Test with one sample table/file flow end-to-end * Provide a short runbook covering setup, rerun steps, IAM/Snowflake roles, and extension notes For a team working within a $750 cap, I would avoid overbuilding the platform in the first pass and focus on getting one reliable, secure, reproducible pipeline working. Once that is proven, additional sources, CDC edge cases, monitoring, and production hardening can be handled as follow-up work if needed. I’m available to review the diagram and confirm the exact scope before starting. Thanks, Kashif

@intelliresponse

As a seasoned Python expert with over a decade in web automation, data extraction, and AI integration, I am the perfect choice to establish your AWS-Snowflake ELT setup. My experience aligns perfectly with your needs for the entire pipeline configuration, security implementation, and proven end-to-end workflow. My expertise in CDC, role-based access control, as well as cost-efficient storage tiers make me uniquely positioned to deliver exactly what you require. I have successfully deployed intricate workflows using technologies similar to what you outlined - Python Glue jobs or DMS and Snowflake DBT models orchestrated by Airflow. Furthermore, I understand the importance of meticulous documentation and clear step-by-step instructions in setting up a robust system. With my help, not only will you have a fully operational AWS → Snowflake ingest path (S3, Glue or DMS, Snowpipe) but also a parameterized dbt project deployed to your repo and scheduled via Airflow. Let's get started on this productive collaborative journey!

@devendrathakur12

Hello, Your architecture is already well planned, so the focus is making every stage reliable, secure, and fully automated from AWS to Snowflake. I have one question: do you want CDC configured only for Amazon RDS through DMS, or should S3 file updates also trigger incremental dbt models automatically? Looking forward to working together, and if you give me this task, your data might finally travel less than your coffee during deployment. Dev S.

@kamran2012

Good to see this project, I will configure the full ingest path from RDS and S3 through Glue/DMS into Snowpipe, wire up your dbt models in Airflow with parameterised profiles, and lock down IAM policies paired with Snowflake role-based access controls. You will get the documented runbook covering every connection so you can extend it without me. One thing I will prioritize: setting up the Snowpipe SQS event notifications correctly from the start, because a misconfigured notification policy is where most auto-ingest setups silently break. Questions: 1) For the CDC sources, are you leaning toward DMS continuous replication or Glue with bookmarks? 2) Is your Airflow instance managed (MWAA) or self-hosted? I am happy to share relevant examples in chat. Let us map out the first step together. Ready to start whenever you are. Kamran

@usmanbashir12100

Hi, I can configure your complete AWS-to-Snowflake ELT pipeline, including Glue/DMS, S3, Snowpipe, dbt, and Airflow, ensuring secure, automated, and reliable end-to-end data ingestion. I have experience with CDC pipelines, IAM policies, Snowflake RBAC, dbt deployments, and Airflow orchestration, and will deliver a fully documented, reproducible setup with a successful end-to-end validation using your sample data. Ready to start immediately and get your pipeline running smoothly. Usman Bashir

@techplusintl

Hi, ★★★ Python / AWS Expert ★★★ 8+ Years of Experience ★★★ I understand you need a hands-on specialist to configure the pipeline linking your AWS stack to Snowflake and dbt. I will set up the entire pipeline, ensuring secure and efficient data flow from Amazon RDS and S3 through Glue jobs or DMS, into Snowflake using Snowpipe. I’ll also implement dbt models and orchestrate everything with Airflow. Deliverables will include: - A working AWS to Snowflake ingest path - A parameterised dbt project deployed to your repo - Documented IAM policies and Snowflake roles - A step-by-step runbook for future reference Ready to get started!

@kumarashish99

As an AWS-certified professional with a strong background in backend development and DevOps engineering, I believe I am a perfect fit for your AWS-Snowflake ELT Setup project. Over the past 5 years, I’ve gained extensive experience working with AWS services, including Glue, DMS, S3 and Snowflake, to design and implement robust cloud architectures. My proficiency in Python will come in handy as we link your AWS stack to Snowflake and employ Glue jobs or DMS for change-data-capture. Moreover, my knowledge of Kubernetes orchestration will enable me to enhance the scalability and efficiency of your cloud stack. With my solid understanding of backend technologies such as Node.js, Python, and PHP, I’ll ensure the successful configuration of your entire pipeline from raw files in S3 through Glue jobs or DMS to Snowflake's dbt models with minimum manual intervention. By availing myself for this project, you're guaranteed a reliable hand that'll not only source required data from Amazon RDS and application buckets efficiently but also manage cost-efficient storage tiers for optimal operation. Choose me for an end-to-end setup guaranteeing security-compliant and cost-effective ELT solution on your AWS account.

@Muhammadzeesha59

Being an experienced AWS and Snowflake specialist, I have a profound understanding of precisely the intricate tasks involved in configuring and securing data pipelines like yours. My proficiency in Python programming with Glue and DMS integration will ensure reliable change-data capture. Using Snowpipe and dbt pipelines, along with Airflow orchestration, my skills seamlessly connect your Amazon RDS, S3 Buckets, Glue jobs, and Snowflake database. I also have substantial experience in designing and configuring IAM roles and policies, using role-based access controls effectively to safeguard your data. Besides that, I pride myself on my cost-efficiency strategies when it comes to storage tiers within Snowflake architecture. This will help optimize your cloud costs without compromising the performance of the system. Moreover, I understand the importance of documentation for reproducibility and extensibility of your setup. Therefore, I will provide you not only with a working pipeline but also with a comprehensive step-by-step runbook and IAM policies that are correctly documented and readily applicable. Your complete satisfaction is my motive; I ensure a well-documented deployment of parameterized dbt project scheduled via Airflow even if it means going the extra mile. Don't hesitate to let me know how I can assist you better!

@sf264

Hello, I came across your project and it caught my interest. I can stand up the actual configuration that will link your AWS stack to Snowflake and dbt. I'd love to discuss the requirements further and get started right away. Best regards, Fahad

@juanpablomacf

You need a specialist who can turn your mapped ELT design into a fully working AWS → Snowflake → dbt pipeline, with Airflow running it end‑to‑end without manual touch. I’ve built similar data flows before, including an AWS CloudFront‑based automotive app where S3, IAM, and cost‑aware storage design were central to the architecture. As Juan Pablo, I’ll configure IAM roles and policies, wire RDS and buckets into S3 via Glue or DMS for CDC, set up Snowpipe auto‑ingest, and deploy a parameterised dbt project that Airflow can orchestrate reliably. I’ll validate the full path with sample tables, document roles and permissions, and deliver a clear runbook so you can rerun, extend, or adjust the pipeline confidently. If this matches the level of hands‑on support you’re looking for, we can align on scope and start.

@rosscarter1011

Hey, the DMS-vs-Glue split for CDC on the RDS side is the part that usually trips people up, so good thing you’ve already got the architecture sketched out. I’d start by getting IAM roles scoped tight between S3 and Snowflake first, then wire Snowpipe auto-ingest before touching the dbt/Airflow scheduling so you’re not debugging two things at once. I’ve dealt with that exact “works manually but breaks on rerun” issue with Airflow-triggered dbt runs before, usually it’s a state or dependency thing. Is your RDS already set up for CDC, or is that still something we’d configure from scratch?

@alizain721

The biggest risk in your setup is not the tools but the handoffs: if CDC streams, S3 staging, Snowpipe notifications, and Airflow-triggered dbt runs are not tied together with least-privilege roles and reproducible artifacts, the pipeline will work once and then break silently. I’ve built production ETL flows where the operational gap between ingest and orchestration caused the most outages, so I’ll treat the job flow and security as a single deliverable. Approach: I will wire S3 staging to Snowflake via Snowpipe auto-ingest (S3 event -> SNS/SQS -> Snowpipe), implement CDC with either DMS or Glue jobs (we’ll pick the best fit), and convert raw files to compressed, partitioned Parquet for cost-efficient storage with S3 lifecycle rules. I’ll create minimal IAM policies and an AWS storage integration for Snowflake, implement Snowflake RBAC roles and grants, and configure Airflow DAGs that run dbt models from your repo using secure connections (Secrets Manager or Airflow connections). Deliverables include the working AWS→Snowflake path, a parameterized dbt project deployed to your repo and scheduled in Airflow, documented IAM and Snowflake roles applied, and a step-by-step runbook with rollback and repro instructions. Relevant example: CrowdAxis involved building reliable ETL cron jobs, normalization into a unified schema, and automated deployments so downstream scoring services ran without manual steps—similar operational needs and deployment discipline to what you describe. I’ll estimate 4–7 business days at $500 assuming account access and sample data on day one. Can you grant an admin-level AWS console role, Snowflake account user with necessary privileges, and Git + Airflow access? Also, do you prefer DMS CDC or Glue-based CDC as the primary ingest?

@emilesd617

Hello, Your AWS → Snowflake ELT architecture aligns well with my experience building secure, production-ready data pipelines on AWS. I can configure the complete end-to-end workflow, including Amazon RDS/S3 ingestion, AWS Glue or DMS for CDC, Snowpipe auto-ingest, dbt transformations, and Airflow orchestration. I'll implement least-privilege IAM roles and Snowflake RBAC, optimize the pipeline for reliability and cost efficiency, and validate the entire process with end-to-end testing using your sample data. My experience includes AWS (S3, RDS, Glue, DMS, IAM), Snowflake, dbt, Apache Airflow, Python ETL development, CDC pipelines, data modeling, and infrastructure documentation. I follow modular, maintainable practices so the solution is easy to extend as your data platform grows. Deliverables will include: • Fully configured AWS → Snowflake ingestion pipeline • Snowpipe auto-ingest and parameterized dbt project • Airflow DAGs for automated orchestration • Secure IAM and Snowflake role configuration • Complete deployment documentation and reproducible runbook • End-to-end validation with sample datasets I'm available to start immediately and can provide regular progress updates throughout the implementation. I look forward to discussing your architecture and helping you deliver a reliable, scalable ELT pipeline.

@MIndlabsAi6

Hi there, I'm Vishal Maharaj, a seasoned professional with 25 years of expertise in Python, AWS, Data Modeling, Cloud Computing, ETL, and Hadoop, based in Perth, Australia. I understand the need for setting up an AWS-Snowflake ELT pipeline seamlessly. My approach involves configuring the entire pipeline securely, from linking AWS sources to Snowflake and dbt models, ensuring smooth data flow and automation under Airflow orchestration. Let's discuss further and kickstart this project. Looking forward to collaborating with you. Cheers, Vishal Maharaj

@godesignpk

Hi, We would like to grab this opportunity and will work till you get 100% satisfied with our work. We are an expert team which have many years of experience on Python, Cloud Computing, Amazon Web Services, Hadoop, Data Warehousing, ETL, Data Modeling, Snowflake Please come over chat and discuss your requirement in a detailed way. Thank You

@techsty2014

This looks like a great fit, We will configure your full AWS to Snowflake ingest path: RDS extraction via DMS with CDC, S3 landing zone, Snowpipe auto-ingest, dbt models, and Airflow orchestration. For the CDC setup, we will configure DMS with full-load-plus-CDC mode and structure the S3 landing zone with date-partitioned prefixes. This lets Snowpipe pick up only new change files, keeping warehouse credit usage low. A couple of quick things to confirm: 1) Is Airflow already deployed (MWAA, self-hosted, or Astronomer), or do we need to set that up as well? 2) How many source tables from RDS will the initial pipeline cover? The number quoted here is a starting estimate. The exact cost and timeline will be confirmed after we go through the full scope together. Looking forward to your response. Best regards, Faizan

@mahads31

As the leader of Solves Inn, I have extensive experience in designing and building robust data pipelines that optimize the use of cloud platforms. Your project aligns perfectly with my skill set. In addition, I am experienced in handling AWS, Snowflake and dbt which will be central to completing this project for you. For your specific needs, I will ensure a secure AWS → Snowflake ingest path (S3, Glue or DMS, Snowpipe) that guarantees data integrity and optimal performance. This entails meticulously creating IAM policies and Snowflake roles that adhere to best practices, tracing the entire pipeline with transparency to guarantee its replicability and scalability. Lastly, what distinguishes us at Solves Inn from others is our dedication to cultivating long-term relationships with our clients. I don't see myself as just completing this job for you but rather I am excited at the prospect of becoming your long-term technology partner by offering you both clarity and execution at every stage of development. Let's embark on this journey together towards building a system designed for lasting success.

@dataspro

Nice to meet you , It is a pleasure to communicate with you. My name is Anthony Muñoz, I am the lead engineer for DSPro IT agency and I would like to offer you my professional services. I have more than 10 years of working as a Backend and Software developer, I have successfully completed numerous jobs similar to yours therefore, and after carefully reading the requirements of your project, I consider this job to be suitable to my area of knowledge and skills. I would love to work together to make this project a reality. I greatly appreciate the time provided and I remain pending for any questions or comments. Feel free to contact me. Greetings

@carlosd178

Hello, As a result of a detailed review of your project requirements, I fully understand the scope and expectations. You need a hands-on AWS to Snowflake ELT pipeline configured end-to-end, secured properly, and proven through Airflow execution. I have experience handling similar data engineering projects and I'm available to start your project right now. I bring strong expertise in Python, AWS, S3, Glue, DMS, IAM, Snowflake, Snowpipe, dbt, Airflow, ETL/ELT, data warehousing, CDC, data modeling, and role-based access control. One of the key challenges in projects like this is making sure the ingest path is reliable from source to Snowflake while keeping permissions secure, costs controlled, and dbt/Airflow execution fully automated. I can configure IAM roles and policies, connect Glue/DMS to S3, set up Snowpipe auto-ingest, deploy parameterized dbt models, and schedule the full workflow in Airflow so it can be rerun from scratch without manual steps. I will also document the IAM policies, Snowflake roles, pipeline flow, and provide a clear runbook for future extension. I have a couple of quick questions. • Do you prefer Glue or DMS as the main CDC approach for RDS? • Is Airflow already deployed, or should I configure the DAGs into your existing environment? I would be glad to discuss further details and am ready to start immediately. Looking forward to hearing from you. Best regards, Carlos