Snowflake & dbt Developer Needed

@ashinnd84

Hello there, we are a team of Full Stack Developers and Data Scientist. Please, send me a message to discuss the work. Thanks Ashish Kumar.

@vishal1145

Your incremental load strategy will fail if you're not handling late-arriving facts correctly. Most dbt implementations I've inherited assume data arrives in order, but real-world source systems don't work that way. This causes duplicate records and broken SCD Type 2 logic that only surfaces after you're in production. Before I extend your models, I need clarity on two things: What's your current approach to handling updates that arrive out of sequence? And are you using Snowflake's clustering keys on your fact tables, or are you relying solely on dbt's incremental materialization? Here's how I'll tighten the build: - SNOWFLAKE OPTIMIZATION: Implement micro-partition pruning through strategic clustering and leverage zero-copy cloning for your staging environment to cut compute costs by 30-40%. - DBT MACROS + JINJA: Build reusable transformation logic that handles late-arriving dimensions and implements proper SCD Type 2 tracking without code duplication across 50+ models. - INCREMENTAL LOAD PATTERNS: Configure merge strategies with proper deduplication logic and add dbt tests that catch data quality issues before they hit your fact tables. - QUERY PROFILING: Use Snowflake's query history and result cache analytics to identify expensive operations and refactor models that scan full tables when they should be reading 2% of partitions. - CI/CD INTEGRATION: Set up slim CI runs in dbt Cloud that only test modified models and their downstream dependencies, reducing pipeline execution time from 45 minutes to under 8. I've built 4 production data warehouses on Snowflake that process 2TB+ daily. I don't take on projects where the existing architecture has fundamental flaws. Let's schedule a 20-minute call to review your current dbt DAG and discuss edge cases before I commit to the backlog.

@Web1devloper

Coming equipped with over 8 years of experience in data analytics and science, I bring a unique blend of skills that make me highly suitable for your Snowflake and dbt project. In addition to my expertise in SQL, I have hands-on experience working with Snowflake warehouses - precisely what you need for this project. Over the years, I've developed a knack for writing clean, well-tested SQL and have even honed my skills on advanced dbt features such as macros,exposures, semantic layer, to name a few. I would like to emphasize my focus on query optimization and performance tuning, which aligns perfectly with the core requirement of your project - keeping costs predictable while ensuring low latency. Furthermore, my proficiency with Data Visualization Tools like PowerBI and Looker confirms not only my ability to deliver results but also means that I can communicate those results in a meaningful way. Past clients across industries such as finance, healthcare, e-commerce have praised my abilities to optimize operations, improve customer understanding and forecast outcomes. I believe this hands-on experience will translate effectively into refining your current schemas and code repositories while enhancing the overall performance of your data-warehouse.

@vinod150987

I have 15+ years of strong IT experience working across .NET and enterprise database technologies, including C#, VB.NET, Java, Python, FastAPI, ASP.NET MVC, ASP.NET Core, REST APIs, AWS Lambda, Angular, IIS, WCF/Web Services, JavaScript, jQuery, HTML, XML, and XSLT. Currently, I work as a Senior Database Developer, primarily supporting SQL Server, PL/SQL, and SSIS-based ETL projects. I have extensive hands-on experience in data migration, data integration, reporting, and production support, working with complex datasets and high-volume systems. I have been actively involved in performance tuning and optimization, including query optimization, indexing strategies, execution plan analysis, and ETL performance improvements.

@sankargan88

I can quickly join and part of your team. I have good experience in snowflake and data side. I have overall 16+ years of IT experience and having an experience working in DBT as recently worked for the UK based bank project. ping me to start the work

@rayt36

Hello, My name is Ray, and I’m a Senior Full Stack Developer with 7+ years’ experience. While my core expertise lies in web and mobile applications, I’ve also developed a strong footing working with databases like MySQL. Building scalable systems and optimizing query performance has always been crucial to my work. My SQL expertise will definitely come in handy. While I am still relatively new to Snowflake and dbt, I have the knowledge and agility to ramp up quickly on new technologies. Thanks to my familiarity with Git-based CI/CD pipelines, data modeling, performance tuning, and testing are integral parts of my skill set - all skills that align perfectly with your requirements. Working with me comes with its own reassurances: clean, maintainable code that aligns with best practices; meticulous documentation; solid architecture; reliable delivery times and long-term support. Should you decide to team up, we’ll be on the same page from Day 1. With your comprehensive acceptance criteria and my commitment towards delivering quality work on time, we can ensure maximum efficiency on this project. Thanks!

@camerone6

Hi , Good morning! I am an expert mobile developer with skills including SQL, Data Warehousing, MySQL, Snowflake and Data Modeling. Please contact me to discuss more regarding this project. Please keep me informed

@toqeer74

Extending existing models in a midway data warehouse build demands a precise grasp of dbt's layer architecture and Snowflake's scalability features. With your implementation already in progress, I can seamlessly integrate new data sources while optimizing the deployment pipeline and ensuring performance targets are met. My approach will focus on extending star/snowflake schemas and conducting rigorous testing to validate run-time metrics. Expect the initial deliverable in 14 days, comprising an enriched dbt project repository, documented run results, and a concise runbook outlining your pipeline orchestration procedures. Happy to share a few early ideas, want me to put something together?

@erdavinder2307

Hi, You’re already past the setup phase—this is about stabilizing, optimizing, and preparing your warehouse for production scale. From your description, the key areas are: Extending dbt models cleanly without breaking existing flows Ensuring incremental models and pipelines run efficiently Optimizing Snowflake usage (cost + performance) Strengthening tests and reliability How I’d approach this: Review existing dbt project structure (models, macros, tests) Extend/refactor models with clear layering (staging → marts) Implement/optimize incremental loads and scheduling Tune Snowflake queries (clustering, pruning, caching) Ensure test coverage + stable CI/CD runs Document key pipeline steps for handoff Focus: Fast, reliable pipelines with predictable performance and clean, maintainable models. I’ve worked on similar data workflows involving SQL optimization, data modeling, and production-ready pipelines. Quick questions: Current bottleneck—query time, cost, or pipeline failures? Are incremental models already in place or partial? Any SLAs for run time? Happy to jump in and start contributing quickly. Best, Davinder

@Surajb0070

Your schemas are in place and pipeline is running — you need someone who jumps in, not someone who needs onboarding on fundamentals. My production SQL experience is PostgreSQL and Oracle rather than Snowflake specifically, but star schema design, query optimization, incremental load patterns, and clean tested SQL are the same game. I led a 500M+ record Oracle-to-PostgreSQL migration, achieved 40% query optimization on financial-grade databases, and work cleanly in Git-based CI/CD. I'd need a day to orient in your dbt repo before touching production models — but the SQL depth is real. Open to a quick technical screen to prove fit before you commit.

@devanshk25

Hello, I can help you build a clean, scalable, and production-ready data pipeline using Snowflake and dbt that is fast, cost-efficient, and easy to maintain. From experience, most Snowflake + dbt projects struggle with three things: inefficient warehouse usage (high cost), messy transformation layers, and lack of testing/documentation. My approach directly solves these: • Well-structured dbt models (staging → intermediate → marts) for clarity and scalability • Performance optimization in Snowflake (clustering, partitioning, query tuning, warehouse sizing) • Incremental models to reduce compute cost and improve speed • Robust testing (schema + data tests) to ensure data reliability • Automated documentation so your team can easily understand and use the data • Seamless integration with your existing data sources (APIs, S3, databases, etc.) I can also set up CI/CD workflows (Git-based) so changes are version-controlled and safely deployed, along with scheduling/orchestration if needed. Whether you need to build from scratch or optimize an existing pipeline, I’ll focus on delivering a system that is not just functional—but efficient, reliable, and production-grade. If you can share your current setup, data sources, and end goals (dashboards, analytics, etc.), I’ll outline a quick execution plan and start immediately. Best regards

@surekhagawade

Hello, I am interested in your Snowflake and dbt data warehouse project. I have strong experience in Data Engineering, SQL, Python, ETL pipelines, Snowflake, data modeling, and cloud-based data platforms. I have worked on building and maintaining data warehouses, designing star and snowflake schemas, creating efficient SQL transformations, and optimizing large-scale data pipelines. I am comfortable with query optimization, incremental loads, performance tuning, and production-ready data workflows. I understand the importance of clean dbt models, testing, scheduling, CI/CD integration, and reliable reporting pipelines. I can help extend your existing models, improve transformation logic, optimize Snowflake performance, and support stable production deployment. I focus on quality delivery, clear communication, and timely completion of work. Looking forward to discussing your project. Best Regards, Surekha Lengare

@pavanreddy097

I have over four years of experience as a Snowflake Administrator and DBA, specializing in building and maintaining production-grade data warehouses. My background is centered on managing complex environments (DEV, TEST, PROD) and developing automated ELT pipelines using Snowpipe, Streams, and Tasks. I am highly proficient in SQL and Jinja, with a focus on writing modular dbt models that are both performant and easy to maintain. I specialize in query optimization, having managed large-scale environment refreshes and performance tuning for high-concurrency schemas. I am ready to step into your existing repository, extend your star schemas, and ensure your deployment pipeline meets strict production thresholds. My goal is to deliver clean, well-tested code accompanied by clear runbooks for seamless orchestration.