Snowflake Experts
matched in minutes by AIHire experts who design cloud data warehouses, build reliable ELT pipelines and optimize Snowflake costs and performance. FRATCH connects you with vetted, available freelancers through fast, precise AI matching.
Meet FRATCH Experts who have recently used Snowflake
Florian R.
Last position:
Global Programme Lead, Ecosystem Separation at Merck Group
Electronics – Surface Solutions | Carve-out of IT, data and system landscape*
Separation of a full business division's IT, data and system landscape following divestment; centrally governed investment envelope in the three-digit m€ range
Laboratory notebook and laboratory analytics platform stream: Palantir Foundry, Snowflake, Signals Notebook, Power BI and connected laboratory instrumentation; site transition completed without interruption to laboratory operations
Decision authority and escalation point for business, IT infrastructure, IT security and vendors; separation executed across globally distributed users and systems, handed over on schedule
Ali A.
Last position:
Founder & Architect at Independent AI R&D
- Fully on-premises LLM document-examination platform for a compliance-critical banking domain: agentic LangGraph pipeline with deterministic verification, every AI judgment structured and source-anchored; ~960 automated tests, zero data egress
- GPU throughput engineering (quantized serving, speculative decoding, prefix caching): 9.5x extraction speed-up, 500+ multi-document case files per day on a single A100
- AI-native EDI/EDIFACT integration platform (~116k LOC Java 25 / Spring Boot 4, 1,900+ tests): LLM-drafted partner mappings machine-verified before go-live (DFDL conformance, field-coverage checks, dry runs), ~99.5% byte match on real customer files — replacing weeks of manual mapping per partner
Mirza K.
Last position:
Agentic Automation and a RAG system
- This project involved extraction of intelligence data to support report writing for a company that provides geopolitical, global, commercial intelligence. The data have been gathered from a number of resources (interview transcripts, online data, internal documents), and then a knowledge base has been build from it. This was the basis of a complex RAG system, that was evaluated against a golden dataset. Agents have been used to find out the contradicting intelligence, the statements supporting each other, and to store back the generated knowledge.
Used: Python, RAG, LangGraph, LangChain, deepeval, MCP
Sarvesh L.
Last position:
Data Analytics for Renewable Energy Integration at Harz University
- Created data pipelines and visualization tools to support sustainable energy decision-making
- Developed insights that could optimize renewable energy deployment and grid integration strategies
Songül D.
Last position:
Freelance SAP BW Consultant at DKV Mobility Services
- Designed and implemented enhancements in SAP BW on HANA 7.5 in the context of CRM migration and S/4HANA and BW/4HANA transformation programs
- Migrated SAPI data sources to the ODP framework as part of the S/4HANA migration
- Delivered SAP ECC data to Snowflake using BW data models and Calculation Views for Power BI analytics
- Integrated SAP and non-SAP data sources (including MS Dynamics)
- Improved reporting transparency through consolidated data models
- Optimized data loading processes for FI-CO data sources, significantly improving load times and system performance
Florian B.
Last position:
Project Management / PMO Consultant
PMO & Project Organization Blueprint for Restructuring
Renewable Energy / Solar Equipment
Technologies / Methods: PMO setup, KPI tracking, project organization, Jira, Confluence
- Developed measures to improve management control during a restruct...
Asım Y.
Last position:
Freelance BI/DWH/ETL Specialist at Akbank
- Setting architectural standards for Informatica Power Center development teams
- Maintenance-performance-health for DWH (Exadata) environments
- Qlik Sense / BO reports architectural standards
- Implementing best practices in ETL tasks
- Documentation ETL standards on Confluence
- Dynamic Data Masking rules for GDPR/KVKK regulations by using Informatica DDM tool
- DWH Data model Power Designer
- Upgrade Qlik Sense versions
- Merge all Informatica server's repository databases on one Oracle DB
Bardiya B.
Last position:
Data Scientist at Rewe Digital GmbH
Statistical Forecasting Algorithm
- Improvement of an statistical probabilistic forecasting algorithm for sales + evaluation
- Migration from R/On-premise to Python/Snowflake
- Productionalization on Snowflake in cooperation with data engineers & DevOps
Monitoring Dashboard
- Data engineering for preparation & provisioning of necessary data/resources on Snowflake
- Development & deployment of a Streamlit dashboard in Snowflake
ML-based Probabilistic Forecasting on Vertex AI
- Development of a ML-based probabilistic forecasting algorithm from scratch
- Implementation of MLOps pipeline in Kubeflow on Google Cloud Vertex AI
Tech Stack: Python, Snowflake/Snowpark, R, Streamlit, Gitlab/Gitlab CICD, Terraform, Google Cloud, Vertex AI (aiplatform SDK, gcloud CLI, feature store, model registry, etc), kubeflow
Ajay Kumar D.
Last position:
Senior BI and Analytics Engineer at Novartis
- Led enterprise reporting modernization by migrating legacy SSRS reporting solutions to Power BI, supporting 500+ business users while ensuring full GDPR/DSGVO compliance.
- Designed and optimized Power BI and Microsoft Fabric semantic models using star schema, dimensional modeling, advanced DAX, and performance optimization techniques, reducing query latency by 25%.
- Delivered 20+ executive and operational dashboards featuring KPI scorecards, drill-through, bookmarks, and row-level security, improving reporting efficiency by 20%.
- Enabled self-service analytics through governed Power BI datasets, dataflows, and gateway architecture, increasing business-led reporting adoption by 35%.
- Configured an incremental refresh policy and query folding for a 50+ million row sales dataset, reducing daily report refresh times by 85%.
- Deployed automated ETL/ELT pipelines using Azure Data Factory, Microsoft Fabric, and Snowflake, reducing reporting delivery timelines by 40% through workflow automation.
- Spearheaded Microsoft Fabric analytics modernization initiatives including lakehouse architecture, OneLake integration, and centralized data platform development, reducing data latency from 2 hours to 20 minutes.
- Translated business requirements from 15+ stakeholders into scalable Power BI semantic models and dashboards, improving reporting consistency and reducing ad-hoc reporting requests by 25%.
- Applied Microsoft Copilot and generative AI tools to accelerate SQL development, DAX authoring, technical documentation, and testing activities, reducing development effort by approximately 15 hours per week.
Alexander Z.
Last position:
Senior Data Solutions Engineer at VMware Inc.
- Architected and deployed private cloud data platform on VMware vSphere, integrating Greenplum MPP, Apache Kafka, Kubernetes, and Apache Solr, and developed real-time ingestion pipelines with Kafka Connect and Schema Registry.
- Led Oracle Exadata to Greenplum migration, rearchitected data models, optimized storage, implemented RabbitMQ with Debezium for CDC, and deployed VectorDB for Generative AI.
- Designed and executed multi-cloud migration PoC across AWS, Azure, and GCP, defined KPIs for throughput, latency, and cost efficiency, executed bulk data transfers, validated analytics and streaming workloads, and delivered full-scale architecture recommendations.
- Assessed legacy on-premises infrastructure and designed modern cloud-native data platforms using Greenplum and containerized microservices, advising on scalability, disaster recovery, and high-availability.
Philipp G.
Last position:
Data Scientist & ML Engineer at Data-Science Factory GmbH
- Building, implementing and selling automated Data Science solutions such as Scorecard Factory and Forecast Factory
- Implementation of automated end-to-end cloud processes
- Development of LLM and NLP models
- Creation of interactive reports
- Support for national and international large corporations as well as medium-sized companies in implementing ML projects
Justina K.
Last position:
Freelance Consultant for Change & Data Transformation at Freelance Fast Data Consulting
Project, Strategic Consulting – building the Data Strategy and Data Governance Policy for the German branch, client (private bank Julius Bär, headquarters Zurich), March 2026 – present
- Design and negotiation of the data strategy with key stakeholders, including obtaining board sign-off (strategic consulting) – in this context, regulatory advice on data regulations in the EU and specifically for Germany. The data strategy includes: Data Lifecycle Management: data capture, data storage, data usage, data retention policy, data quality incident management
- Definition of milestones and technical feasibility for implementing TOM for the data strategy, data quality checks, metrics, and a metadata inventory to ensure the bank’s compliance with DORA, BCBS239, and MaRisk requirements.
Core project data change, client: (ING Bank, Frankfurt am Main), March – December 2025
- Concept development and solution design for new end-to-end processes including technical interfaces
- Definition of synchronization logic and data flows between legacy and target systems (decommissioning of legacy systems)
- Analysis and validation of data models
- Stakeholder communication with product owners, feature engineers, UX designers, and operational teams for decision-making
- Analytics and impact assessments, e.g. to assess downstream effects and regulatory requirements
- Documentation and comments on technical and business requirements to support implementation in agile squads
Project digitalization of a user group, client: (ING Bank, Frankfurt am Main), as Interim Product Owner, Jan 2025 – present
- Co-shaping key decisions on data architecture and process logic in the context of historized data and user login functionality
- Development of business solution concepts for migration to the target system, including system integration and data flows
- Support with analytics and impact analyses, especially regarding the ability to provide information to law enforcement authorities
- Active coordination with stakeholders from different squads to support decision-making and ensure regulatory requirements are met
- Creation of test scenarios for operational teams and backend systems in the area of API management using Postman and Bruno.
Saman S.
Last position:
AI Product Builder at Instalemon.com
- Architected and built an agentic creative automation platform on Mastra, with a custom RAG pipeline, custom hooks, tools and skills, Chroma for vector storage, and a MongoDB/Express backend.
- Built the agent orchestration layer powering Pixomi's multi-agent workspace, including 72 custom marketing skills, tools and hooks, and a custom context-management pipeline.
- Designed and implemented evals and observability through Mastra studio.
- Onboarded 10 pilot SMB customers producing 10x publish-ready creative output per campaign versus manual production in 3 months.
- Ran customer discovery and pilot feedback loops to shape the roadmap for an AI-native, workflow-based creation platform.
Laurin H.
Last position:
Software Architect (Freelance) at Care4Sure
- Delivered MVP-focused full-stack architecture for a health-sector client: Vite/React frontend, backend services on Google Cloud Run, and Supabase for database plus IAM/authentication.
- Supported product requirements engineering and prioritized cost-aware workload placement, implementing browser-side/edge computation where feasible before moving logic to backend services.
Sander O.
Last position:
Interim Head of Contract Management at Enpal
- Directed the contracts management function for Europe's largest renewable energy portfolio, 10 FTE
- Implemented process automations by architecting scalable, data-driven workflows leveraging AI and traditional automation
Discover over 15,000 top freelancers
Statistics of experts using Snowflake
Aggregated from the professional profiles of matched freelancers.
Experience
16 years
Position duration
3.1 years
Positions per freelancer
10
Top business areas
Information Technology, Business Intelligence, Product Development
Top industries
Information Technology, Professional Services, Banking and Finance
Certification focus areas
Information Technology, Business Intelligence, Project Management
Bachelor's degree or higher
96%
Master's degree or higher
61%
Doctorate
8%
Certifications per freelancer
3
Most common languages
German, English, French
Speak two or more languages
98%
Based on our profile pool as of 16 Oct 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows the share of experts charging within that range.
Average rates of experts using Snowflake
Rates are based on recent contracts and do not include FRATCH margin.
The average daily rate is the mean of all daily rates from recent contracts of comparable freelancers on our platform.
The median daily rate is the middle value of all daily rates — half of comparable freelancers charge less, half charge more. Unlike the average, it is barely affected by outliers.
Calculated based on our freelancers’ daily rates as of 16 Oct 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Snowflake experts industry focus
See which industries our matched freelancers work in most often — every figure is calculated live from the freelancers on FRATCH.
- Information Technology (82%)
- Professional Services (50%)
- Banking and Finance (47%)
- Retail (43%)
- Healthcare (37%)
- Manufacturing (32%)
- Automotive (32%)
- Education (28%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
What Snowflake is
Snowflake is a fully managed cloud data platform for storing, processing and sharing structured and semi-structured data. Its separate storage and compute architecture lets teams scale workloads independently across major cloud environments. Companies use it for analytics, reporting, data science and governed data sharing.
Core workloads
Snowflake supports central data warehouses, lakehouse-style architectures and operational analytics. It handles batch and near-real-time ingestion, transformation, secure data sharing and machine learning preparation.
- Consolidating data from applications, APIs and files
- Building reporting layers for business teams
- Supporting customer, product and financial analytics
- Publishing governed datasets to internal or external users
Ecosystem and tooling
Strong Snowflake specialists work across SQL, Python and the Snowpark framework. They commonly connect dbt, Airflow, Fivetran, Matillion, Kafka, BI tools and cloud storage to Snowflake. They also understand streams, tasks, dynamic tables, stages, warehouses, resource monitors and Snowflake Cortex capabilities where relevant.
When companies need experts
Companies often bring in freelance Snowflake professionals during a migration from an on-premises warehouse, a new analytics platform rollout or a major change in data governance. They may also need help when warehouse costs rise, pipelines become unreliable or teams cannot agree on a clear data model.
- Assessing an existing warehouse and migration path
- Designing schemas, roles and workload isolation
- Improving slow queries and inefficient transformations
- Establishing testing, deployment and monitoring practices
Skills that distinguish strong specialists
A capable professional combines dimensional modeling with practical cloud operations. They can explain when to use transient, temporary or permanent tables, tune warehouses without masking poor SQL, and apply masking policies, row access policies and secure views appropriately. They also document lineage, ownership, recovery plans and expected operating costs.
Project fit and delivery
Snowflake work may cover a focused optimization, a complete platform build or ongoing support for data teams. Good specialists define source assumptions, data freshness targets, access boundaries and acceptance checks before changing production workloads. They communicate clearly with analysts, application teams and security stakeholders, whether collaboration is remote or on-site.
Frequently asked questions
Curious about Snowflake? Here are the answers that come up again and again.
Snowflake is used to store and analyze data in the cloud without managing the underlying database infrastructure. Companies use it for enterprise reporting, customer analytics, data integration, data science preparation and secure data sharing.
Snowflake is traditionally centered on a managed SQL warehouse and governed analytics, while Databricks is strongly associated with Spark-based processing, notebooks and lakehouse workloads. The right choice depends on data formats, processing patterns, team skills and governance needs; many organizations use both.
A strong Snowflake specialist often brings SQL, dimensional modeling, Python, dbt and orchestration experience. Knowledge of cloud storage, identity management, CI/CD, data quality, observability and BI tools is also valuable for production delivery.
The required depth depends on the scope. A focused reporting layer may need a specialist with targeted Snowflake delivery experience, while a migration or governance redesign calls for a professional who has handled security, workload management, deployment and recovery in comparable environments.
Yes, most Snowflake tasks can be completed remotely because access, documentation and collaboration happen through cloud tools. On-site sessions can still help with discovery, stakeholder workshops or sensitive architecture decisions, especially when teams operate across different languages or time zones.
Ask how the specialist approaches data modeling, access control, testing, monitoring and cost management. A credible Snowflake professional should explain trade-offs clearly, show how changes are deployed safely and connect technical decisions to freshness, reliability and business use.
Snowflake Data Cloud is the broader product and ecosystem name, while Snowflake commonly refers to the platform itself. The service includes data storage and processing as well as capabilities for sharing, governance, application development and collaboration across organizations.
A Snowflake expert can deliver a warehouse design, migration plan, ingestion pipelines, dbt models, security configuration, performance review or cost-control framework. They may also provide documentation, automated tests, deployment workflows and operational runbooks for the internal team.
The average hourly rate of freelancers who have used Snowflake in their recent projects is 98 €, which corresponds to a daily rate of about 780 € based on an 8-hour working day.
Of the freelancers who have used Snowflake in their recent projects, 96% hold at least a Bachelor's degree, 61% hold at least a Master's degree, and 8% hold a doctorate.
On average, freelancers who have used Snowflake in their recent projects have 16 years of professional experience, with a single engagement typically lasting around 3.1 years.
The most common languages among freelancers who have used Snowflake in their recent projects are German (97%), English (97%), and French (18%).
The most common industries among freelancers who have used Snowflake in their recent projects are Information Technology (82%), Professional Services (50%), and Banking and Finance (47%).
The most common business areas among freelancers who have used Snowflake in their recent projects are Information Technology (95%), Business Intelligence (88%), and Product Development (69%).
Main locations of FRATCH Experts, who have recently used Snowflake
Our freelancers and interim experts are at home all over Germany — available on-site in Berlin, Hamburg, Munich and every major business hub, or fully remote. Choose a city to discover matched specialists, local market insights and up-to-date availability.
Berlin 
Hamburg 
Munich 
Frankfurt 
Dusseldorf 
Berlin Hamburg Munich Cologne Frankfurt Stuttgart Dusseldorf Leipzig Dortmund Essen Bremen Dresden Hanover Nuremberg In Austria our freelancers and interim experts support companies from Vienna to Graz — on-site where your project needs them, or fully remote. Choose a city to discover matched specialists, local market insights and up-to-date availability.
Vienna Graz Across Switzerland our specialists are active in Zurich, Geneva, Basel and Bern — working on-site or fully remote. Choose a city to discover matched specialists, local market insights and up-to-date availability.
Zurich Geneva Basel Bern Countries:
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Philipp Thomaschewski
FRATCH CEO
