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Recently Added Data Snowflake Developers in our Network

Abhishek Srivastava

Abhishek SrivastavaProfile Badge IC

Data Engineer3 Years of Exp
  • Python
  • machine_learning
  • SQL
  • NumPy
  • pandas
  • ETL
  • AWS EC2
  • AWS Glue
  • View all (10)

Data Engineer with 2.5+ years of experience in the tech industry. Proven ability to use cloud computing platforms to store, process, and analyze data. Expertise in data migration, and data warehousing. Strong problem-solving and analytical skills.

Harsha vardhan Reddy

Harsha vardhan ReddyProfile Badge IC

Software Engineer5.2 Years of Exp
  • Git
  • Unix
  • Snowflake
  • dbt
  • Abinitio
  • AWS S3
  • EDM
  • Jira
  • Oracle
  • Putty
  • SQL
  • View all (14)

Dynamic and experienced professional with a solid background in Snowflake, AWS S3 and DBT seeking a challenging role where I can leverage my expertise to drive data-driven solutions and contribute to the success.

Sunkara Yasasvi

Sunkara YasasviProfile Badge IC

Software Engineer6.2 Years of Exp
  • SQL
  • Python
  • Shell Scripting
  • 2D
  • Bitbucket
  • PySpark
  • Confluence
  • View all (11)

Experienced IT professional with proven track record of four years, adept in Snowflake, legacy data systems, SQL, data warehousing, big data technologies and ETL processes. Seeking avenues to further enrich my expertise by engaging with cutting-edge data technologies.

Srinivas sukka

Srinivas sukkaProfile Badge IC

Lead Data Engineer10 Years of Exp
  • Data Modelling
  • SQL Queries
  • Data Warehousing
  • NoSQL databases
  • View all (6)

Total 10+ years of experience in developing enterprise data warehousing applications with a focus on implementing end to end Snowflake data warehouse solutions.

Muhammed Suhail EK

Muhammed Suhail EKProfile Badge IC

Data Engineer4 Years of Exp

As a Senior Data Engineer at EY, I lead and ensure the delivery of high-quality data solutions to our clients, collaborating with cross-functional teams and leveraging Azure Databricks, Spark, Python, and Azure Cloud technologies. I have saved time and money by implementing automations for data integrity validations and infrastructure management. In my role as an Azure Data Engineer at EY, I engineered a new analytic platform with a central marketplace for analytics discovery and a robust engine for deploying repeatable data solutions.I have a Bachelor of Technology in Computer Science from APJ Abdul Kalam Technological University, where I gained a solid foundation in data engineering, data integration, data transformation, and machine learning algorithms. I am also certified in Python, Cloud, and Databricks. I am passionate about learning and exploring new tech opportunities, and I am always eager to expand my skillset and knowledge. 

Janani Sivasubramanian

Janani SivasubramanianProfile Badge IC

Snowflake Data Developer4 Years of Exp
  • Data Analysis
  • ETL processes
  • Data Modeling
  • Performance Tuning
  • View all (6)

To seek a challenging role to apply advanced analytics techniques, collaborate with cross-functional teams, and contribute to organizational growth by leveraging data-driven strategies and solutions.

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What Founders & Engineering Leaders Say About Us

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Uplers earned our trust by listening to our problems and finding the perfect talent for our organization.

Barış Ağaçdan
Director
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Uplers helped to source and bring out the top talent in India, any kind of high-level role requirement in terms of skills is always sourced based on the job description we share. The profiles of highly vetted experts were received within a couple of days. It has been credible in terms of scaling our team out of India.

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Uplers efficient, quick process and targeted approach helped us find the right talents quickly. The professionals they provided were not only skilled but also a great fit for our team.

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Hire Snowflake Developers to Simplify Complex Data Challenges

As businesses scale and the data grows exponentially, managing and analyzing data can become a significant challenge. This is where Snowflake, a powerful cloud-based data platform, becomes essential.

Frequently Asked Questions

Uplers ensures a seamless hiring experience by combining AI and human intelligence to vet top-quality Snowflake developers. You receive carefully shortlisted profiles within 48 hours and can onboard the right talent in as little as 2 weeks, helping you hire faster without compromising on quality.

You can receive the top 1% shortlisted profiles within 48 hours through Uplers. Once you finalize the most suitable Snowflake developer, Uplers handles the entire hiring and onboarding process. Depending on your requirements and decision-making timeline, onboarding typically takes 2-4 weeks.

The modes of communication through which you can get in touch with a hired Snowflake Developer include:

  • Email
  • Phone
  • Messaging apps such as WhatsApp, Slack, or Microsoft Teams

If the developer doesn’t meet your expectations, we offer a 90-day replacement guarantee for full-time hires and a lifetime replacement for contract roles, at no additional cost. Additionally, you can opt for a 30-day cancellation policy with no extra charges, giving you complete flexibility to make changes as needed.

The average cost of hiring a Snowflake Developer from Uplers starts at $2500. The number varies depending on the experience level of the developer as well as your requirements.

View Our Pricing For 2025 - 26

At Uplers, candidates are thoroughly evaluated for communication skills and overall suitability for collaboration. Beyond language proficiency, cultural alignment is also assessed to help ensure seamless integration with your team, fostering effective communication, collaboration, and long-term success.

Our network includes Snowflake specialists across a range of use cases. You can hire Snowflake data engineers to build ELT pipelines, implement dbt transformations, and orchestrate data workflows, Snowflake developers and solution architects to design scalable data warehouse architectures, optimize queries, and model data, Snowflake DBAs to manage performance, security, governance, and cost optimization, and Snowpark developers to build Python and Java applications that run natively within Snowflake. Whether you need data engineering, platform administration, or advanced analytics development, we can connect you with specialists who match your requirements.

Communication is essential for Snowflake developers, as they work closely with data engineers, analysts, BI teams, and business stakeholders. Strong Snowflake developers can clearly explain data models, present warehouse performance and cost optimization recommendations, and communicate the impact of pipeline issues or data quality problems. They also collaborate effectively during architecture discussions and requirements gathering to ensure scalable, reliable, and business-ready data solutions.

Yes. Your cloud data warehouse choice directly influences the skills your developer should have. Snowflake is ideal for multi-cloud environments, scalable analytics, and advanced data sharing. Google BigQuery is a serverless warehouse optimized for large-scale analytics and Google Cloud ecosystems, while Amazon Redshift integrates closely with AWS data services and workloads. Although the core data engineering concepts are similar, each platform has its own architecture, optimization techniques, and tooling. Hiring a developer with hands-on experience in your chosen platform helps reduce ramp-up time and ensures better performance, scalability, and cost optimization.

Yes. Many Snowflake developers in our network use dbt (data build tool) to build scalable, well-governed analytics workflows on Snowflake. They develop modular SQL transformations, design staging, intermediate, and mart layers, implement incremental models, automate data quality testing, and create reusable dbt macros. By combining dbt with Snowflake, they help organizations build reliable, maintainable, and scalable analytics platforms that support business intelligence, reporting, and data-driven decision-making.

Look beyond certifications by evaluating a developer's ability to design, optimize, and manage production-scale Snowflake environments. Strong Snowflake developers should demonstrate expertise in query performance tuning, data modeling, dbt transformations, incremental pipeline design, workload optimization, and cost management. They should also understand how to build scalable, reliable, and efficient analytics platforms that balance performance, governance, and operational costs.

Yes. Many Snowflake developers in our network specialize in query performance optimization using features such as clustering keys, Search Optimization Service, and Query Profile analysis. They optimize SQL queries, improve micro-partition pruning, reduce unnecessary data scans, tune virtual warehouse performance, and implement cost-efficient strategies to accelerate analytics workloads. Whether you're troubleshooting slow queries or optimizing large-scale data warehouses, they can help improve both performance and efficiency.

Yes. Snowflake developers in our network have experience optimizing Snowflake costs through efficient virtual warehouse management, resource monitors, and credit consumption optimization. They right-size virtual warehouses, configure auto-suspend and auto-resume settings, monitor warehouse usage, optimize query execution, and implement cost governance strategies to improve performance while controlling compute and storage expenses across Snowflake environments.

Yes. Developers in our network have experience with advanced Snowflake capabilities, including Snowpark, Dynamic Tables, Streams & Tasks, and Snowflake Cortex AI. They build scalable data applications, automate data pipelines, develop Python-based transformations within Snowflake, implement change data capture (CDC) workflows, and leverage built-in AI capabilities for tasks such as text analysis, embeddings, and intelligent data processing all while keeping data securely within the Snowflake platform.

Yes. Snowflake developers in our network have experience implementing Snowflake security using role-based access control (RBAC), dynamic data masking, row-level security, and network policies. They design secure access models, protect sensitive data, enforce least-privilege permissions, configure secure network access, and implement governance practices that support regulatory and organizational compliance while enabling secure data access across teams.