Amazon Athena Expert in Munich
for faster analytics with vetted, available freelancersHire experts who query S3 data with Athena, design reliable AWS Glue Data Catalog structures and optimize SQL for Parquet, Iceberg and partitioned datasets. FRATCH matches you quickly and precisely with vetted, available freelancers.
Meet FRATCH Experts in Munich, who have recently used Amazon Athena
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
Florian B.
Last position:
Business Architect — Project Organization Blueprint for Restructuring
Tasks & results:
- Developed measures to improve management steering during a restructuring program (approx. 80 participants)
- Set up a PMO to ensure transparency, reporting and data-driven decisions
- Created an integration template to transfer team s...
Suyash S.
Last position:
Data Analyst - Reporting & Analytics at SIXT SE
- Developed & maintained customer analytical reporting solutions to identify revenue trends, performance drivers, risks & optimization opportunities to ensure data driven decision making across Sales, Finance, Product, Data Engineering & Controlling.
- Defined & analyzed customer trends & performance metrics to identify root causes behind variances, anomalies & emerging risks across business domains to deliver actionable recommendations.
- Developed & owned analytical data models & reporting layers to ensure scalability, performance & analytical robustness to support executive & operational reporting across business domains.
- Planned, tracked & executed projects by ensuring adherence to timelines, data accuracy, consistency, deliverables, reliability & data quality standards through rigorous validation & reconciliation processes.
- Raised the analytical maturity by formalizing analytical workflows, documenting data processes & standard operating procedures (SOPs) & conducting training sessions to drive adoption of self-service analytics & embed a data driven culture across operational and business teams.
- Took ownership of the end-to-end lifecycle roadmap from requirement gathering, collection, transformation, developing robust business logics to data storytelling & stakeholder delivery.
- Converted complexity into structured clarity by translating requirements & business processes into analytical recommendations to ensure alignment between non-technical & technical stakeholders.
- Conducted advanced SQL based analysis of complex business datasets to uncover trends, correlations & performance improvement opportunities.
- Drove process automation & efficiency improvements by leveraging Python, SQL optimization & AI assisted tools to reduce processing time & increase reliability across analytical & operational workflows.
- Standardized KPI definitions & reporting logic to ensure consistency & trust across reporting solutions.
- Developed process monitoring dashboards & analyses to identify inefficiencies, bottlenecks & compliance deviations across end-to-end business processes to derive actionable recommendations for process improvement & automation.
Any-Arlene N.
Last position:
Co-Founder · Data Engineering & Backend at zirikana (Kirundi Bible Web App) – Civic Technology
- Built a Python pipeline that converts lectionary web content into structured daily JSON, applying liturgical-calendar rules for accurate weekday and Sunday coverage.
- Shipped a read-only FastAPI REST API with shared Pydantic models and delivered a Kirundi-first web client for browser and mobile use.
- Owned the data layer and backend architecture, collaborating closely on system architecture and interfaces while automating refreshes with GitHub Actions and validating the ETL with pytest.
- Impact: Created a reliable, API-driven source of truth for daily Bible readings in Kirundi, enabling consistent access to previously unstructured content.
Eli R.
Last position:
Technical co-founder at AskTheLaws
- Create an AI legal assistant with modern ML capabilities.
- Implement RAG architecture, with data pipelines for legal data search.
- Use AWS Bedrock for LLM and embedding models and LangChain/LangGraph
- Python with FastApi for backend and React for frontend
Clarissa H.
Last position:
AI Trainer at Komdis GmbH
- Led comprehensive AI workshops for professionals, focusing on AI-driven process automation.
- Tech Stack: n8n, Make, LLMs (OpenAI, Anthropic), Prompt Engineering, Process Mapping Tools.
Thorsten G.
Last position:
Head of Real Estate Products | Technical Program Lead
- Program lead for a multi-year strategic partnership (~€9M device volume), reporting to the CTO (later CEO) and acting as primary executive interface to partner leadership.
- Owned cross-system delivery across firmware, hardware, cloud backend, manufacturing and partner engineering teams for two IoT products; improved system stability and observability to support reliable large-scale field operations (125k+ devices).
- Negotiated program roadmap and scope with partner leadership, aligning delivery commitments across hardware, firmware and cloud.
- Stabilized a strained executive partnership by restoring delivery reliability and establishing clear governance and scope boundaries.
- Delivered telemetry analysis system (Python, AWS) required by partner contract to detect malfunctioning heating systems and operational issues across deployed devices.
Max R.
Last position:
Cloud (AWS) | AI | DevOps | Data at Boehringer Ingelheim
- Architected and implemented an enterprise-grade AI Agent Platform leveraging Retrieval Augmented Generation (RAG) architecture to enhance clinical data insights.
- Established robust CI/CD pipelines for LLM applications using CDK and Jenkins, significantly reducing deployment times.
- Implemented comprehensive observability solutions that increased agent reliability across pharmaceutical environments.
- Designed scalable AI workflows with advanced orchestration that optimized context handling for enterprise data sources.
- Technologies: AI Agents (LangChain, LangGraph, Bedrock, Smolagents, Streamlit); LLM Operations (Tracing, Testing, Evaluation, LangSmith, LangFuse); Infrastructure-As-Code (AWS CDK, Terraform, Typescript, Jenkins); Vectors, Embeddings, RAG (OpenSearch, pgvector, PDF Extraction)
Christof N.
Last position:
Senior Developer at Otto GmbH
- Further development of personalized advertising spaces on the Otto web shop
- Full-stack development in a Kanban-driven team of about 15 people
- Technologies: Microservices, Kotlin, Spring, Spring Boot, Gradle, MongoDB, HTML, JS, Node, SCSS, AWS
- Development process: Kanban; continuous integration with AWS CodePipeline and GitHub Actions
Discover over 15,000 top freelancers
Statistics of experts using Amazon Athena
Aggregated from the professional profiles of matched freelancers.
Experience
14 years (Germany: 15 years)
Position duration
1.8 years (Germany: 1.9 years)
Positions per freelancer
12 (Germany: 9)
Top business areas
Information Technology, Product Development, Business Intelligence
Top industries
Information Technology, Automotive, Retail
Certification focus areas
Information Technology, Product Development, Business Intelligence
Bachelor's degree or higher
89% (Germany: 90%)
Master's degree or higher
78% (Germany: 52%)
Doctorate
11% (Germany: 10%)
Certifications per freelancer
3 (Germany: 4)
Most common languages
German, English, Spanish
Speak two or more languages
100%
Based on our profile pool as of 19 Sep 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology in Munich are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows how many freelancers charge within that range.
Average rates of experts in Munich using Amazon Athena
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 19 Sep 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Amazon Athena 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 (89%)
- Automotive (78%)
- Retail (67%)
- Energy (44%)
- Banking and Finance (44%)
- Manufacturing (44%)
- Telecommunication (44%)
- Aerospace and Defense (33%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
Serverless analytics
Amazon Athena is a serverless query service for analyzing data directly in Amazon S3 with standard SQL. Companies use it to explore data lakes, build reporting datasets and support analytics without provisioning database servers. Charges are based on query usage, so sound data layout and query design matter.
Data lake foundations
Athena works with structured and semi-structured files in S3, including Parquet, ORC, CSV and JSON. Specialists organize schemas through the AWS Glue Data Catalog and define tables, partitions, views and permissions that keep shared datasets discoverable. They also apply formats such as Apache Iceberg where teams need transactional lakehouse features.
AWS ecosystem
Athena projects often connect several AWS services and open standards:
- S3 storage, lifecycle rules and folder conventions
- AWS Glue crawlers, catalogs and ETL workflows
- Lake Formation permissions and governed data access
- QuickSight dashboards, notebooks and BI tools
- CloudTrail, IAM and query workgroup controls
Professionals may also work with Apache Spark, dbt, Terraform and orchestration services when Athena is part of a wider data platform.
Typical delivery
Freelance specialists create external tables, reusable views and curated reporting layers for finance, retail, logistics, manufacturing and other data-intensive operations. They tune partition projection, column selection, file compression and joins to improve query efficiency. Deliverables can include SQL models, catalog conventions, access policies, dashboards and operating documentation.
When to hire
Companies usually bring in independent expertise when S3 data has grown difficult to query, dashboards return inconsistent results or a migration from a warehouse needs a practical lake architecture. Strong support is also useful before introducing Iceberg, centralizing governance or connecting Athena to a new BI workflow. In Munich, remote collaboration can work well when documentation and communication are clear; some teams still need on-site workshops.
What strong experts bring
Look for professionals who can explain query plans, data formats and AWS permissions in terms your team can act on. They should test schemas against real files, handle late or malformed data and make SQL maintainable rather than merely functional. A good specialist also defines ownership, monitors workgroups and leaves behind patterns that internal teams can operate confidently.
Frequently asked questions
What clients ask us most about Amazon Athena — answered in short.
Amazon Athena is used to query data stored in Amazon S3 with SQL, without managing database infrastructure. Companies use it for ad hoc analysis, data lake reporting, operational insights and datasets that feed BI tools such as QuickSight.
Amazon Athena queries data in place, while a traditional warehouse usually loads data into managed storage designed for repeated analytical workloads. Athena can simplify exploration and reduce infrastructure management, but a warehouse may offer more predictable performance for highly concurrent, governed reporting.
A strong Amazon Athena specialist usually understands S3 data organization, AWS Glue, IAM, Lake Formation and SQL optimization. Experience with Parquet, Apache Iceberg, Terraform, orchestration and a BI tool is valuable when Athena sits inside a broader data platform.
The right level depends on the work: a focused query or table task needs less planning than a governed data lake migration. A capable Amazon Athena professional should have delivered comparable schemas, permissions and performance improvements, and should be able to show how they tested the result.
Amazon Athena work is often suitable for remote collaboration because queries, schemas and infrastructure can be reviewed through shared AWS environments and version control. Munich teams should agree on documentation, meeting language, access controls and whether occasional on-site workshops are required.
Ask an Amazon Athena professional to explain partitioning, file formats, query plans and failure handling using a relevant example. Quality is visible in clear schemas, reproducible SQL, controlled permissions, sensible monitoring and documentation that another specialist can maintain.
Amazon Athena is complementary to AWS Glue and can complement or compete with Amazon Redshift depending on the workload. Glue helps catalog and transform data, while Redshift provides a managed warehouse; Athena is most suitable when teams want SQL access to data already stored in S3.
Freelancers working with Amazon Athena commonly build external tables, repair catalog metadata, optimize Parquet datasets and connect query results to reporting tools. They may also implement Iceberg tables, automate infrastructure and establish governance across S3-based data lakes.
The average hourly rate of freelancers in Munich, Germany who have used Amazon Athena in their recent projects is 110 €, which corresponds to a daily rate of about 879 € based on an 8-hour working day.
Of the freelancers in Munich, Germany who have used Amazon Athena in their recent projects, 89% hold at least a Bachelor's degree, 78% hold at least a Master's degree, and 11% hold a doctorate.
On average, freelancers in Munich, Germany who have used Amazon Athena in their recent projects have 14 years of professional experience, with a single engagement typically lasting around 1.8 years.
The most common languages among freelancers in Munich, Germany who have used Amazon Athena in their recent projects are German (100%), English (100%), and Spanish (22%).
The most common industries among freelancers in Munich, Germany who have used Amazon Athena in their recent projects are Information Technology (89%), Automotive (78%), and Retail (67%).
The most common business areas among freelancers in Munich, Germany who have used Amazon Athena in their recent projects are Information Technology (100%), Product Development (89%), and Business Intelligence (78%).
Main locations of FRATCH Experts, who have recently used Amazon Athena
Our freelancers and interim experts are at home across the DACH region — available on-site in the major business hubs or fully remote. Choose a location to discover matched specialists, local market insights and up-to-date availability.
Berlin Hamburg 
Munich Cologne Frankfurt Stuttgart Dusseldorf Leipzig Dortmund Essen Bremen Dresden Hanover Nuremberg 
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Philipp Thomaschewski
FRATCH CEO
