Unity Catalog Experts in Germany
matched in minutes with vetted, available freelancersHire experts who design governed data platforms, manage Databricks workspaces, and secure analytics access with Unity Catalog. FRATCH matches you quickly and precisely with vetted, available freelancers for your project.
Meet FRATCH Experts in Germany, who have recently used Unity Catalog
Murad K.
Last position:
Senior AI/ML Engineer at Quantistry GmbH
- Led end-to-end delivery of ML/AI applications for the QuantistryLab simulation platform, from requirements definition and solution design to development, testing, deployment, and production support, coordinating efforts across back-end, DevOps, and ML teams
- Designed and implemented a compound search system with an open-weights LLM, the Pydantic AI agent framework, and the Model Context Protocol (MCP), exposing it through FastAPI endpoints
- Deployed and configured vLLM-based LLM serving on Kubernetes
- Built CI/CD pipelines and Helm charts to automate deployments across staging and production environments
- Instrumented the search system with OpenTelemetry spans and traces, integrating with the Honeycomb observability platform to monitor component-level latency and functional errors
- Developed a custom evaluation dataset and implemented evaluations for retrieval relevance, answer correctness, tool-call accuracy, and end-to-end task success
- Reduced infrared spectrum prediction time by 83% (from 60 to 10 minutes) by replacing a quantum-mechanical model with a pretrained graph neural network; fine-tuned the model using PyTorch, built and containerized the inference pipeline with Docker, and integrated it into the platform
- Implemented an MLflow model registry with MinIO-backed artifact storage
- Advised sales and science teams on ML/AI applications for prospective client projects, providing technical expertise to shape proposed solutions and prototypes
Technologies: AWS, Hetzner, Kubernetes, Helm, Docker, vLLM, Pydantic AI, MCP, Qwen, Llama 3, MLflow, MinIO, GitHub Actions, Python, FastAPI, OpenTelemetry, Honeycomb, PyTorch, Polars, pytest
Daryoosh D.
Last position:
FP&A Data & AI Architect at Epta Group
Scope: Embedded as FP&A Data & AI Architect within the Finance function of a major European refrigeration manufacturer, leading the transformation of manual, fragmented financial reporting into an automated, governance-driven intelligence platform. Driving the shift from Excel-based controlling to structured data architecture, Power BI analytics, and AI-assisted financial operations.
Financial Data Integrity & ERP Governance
- Initiated and led GL vs. subledger reconciliation investigations, identifying and resolving structural mismatches between General Ledger and subledger data that had gone undetected prior to engagement
- Conducted asset analysis to identify items missing from General Ledger postings, surfacing gaps in fixed asset tracking and period-end completeness
- Validated SAP reports, establishing baseline data quality standards for Finance team consumption
- Established systematic SAP data validation framework ensuring ongoing integrity between ERP postings and downstream reporting outputs
Finance Reporting Transformation
- Designed and implemented a structured Transformation Project approach for converting manual Finance reports into fully automated processes
- Created and owns the Data Reporting Audit Log; a centralized tracking system capturing report owners, stakeholders, data sources, manual effort estimates, and automation opportunity scores across the Finance function
- Mapped the full reporting landscape identifying quick-win automation targets and strategic Power BI migration candidates
- Actively reducing manual Excel and PowerPoint dependency across FP&A workflows; replacing point-in-time snapshots with live, governed data models
Power BI & Analytics Enablement
- Introduced and presented Power BI as the strategic reporting platform to Finance leadership, building internal buy-in for the BI transformation roadmap
- Designed initial Power BI architecture aligned with SAP, Salesforce and Oracle data structures and FP&A reporting requirements
- Established report ownership, governance documentation, and data lineage standards enabling sustainable self-service analytics across the Finance team
Transformation Infrastructure & Collaboration
- Configured and deployed Jira as the transformation project management hub, establishing structured sprint workflows, backlog management, and progress visibility for Finance IT initiatives
- Proposed and initiated a dedicated FP&A Communication & Transformation Hub, a structured cross-functional forum aligning Finance, IT, and business stakeholders around the reporting transformation roadmap
- Positioned the Finance function as an active driver of data governance and digital transformation within the broader organization
Outcomes
- GL/subledger reconciliation gaps identified and investigation framework established within first two weeks of engagement
- Data Reporting Audit Log deployed; first structured inventory of Finance reporting landscape in company history
- Power BI transformation roadmap presented and approved by Finance leadership
- Jira-based project governance live; Finance transformation now tracked with full sprint visibility
Technologies: SAP FI/CO · Power BI · DAX · SQL · Excel (advanced) · Power Query (M) · Power Automate · VBA · Jira · Microsoft 365 · SharePoint · Salesforce (Sales Data) · Oracle HCM · Python
Alexander B.
Last position:
Senior Data Engineer at RWE AG
Architected and maintained data products for renewable energy operations, covering wind turbine, grid-meter, and weather data. Built scalable ETL/ELT pipelines in Azure Databricks using Delta Lake (bronze/silver/gold layers) and processed data in various formats, including structured and semi-structured data. Contributed to a data quality framework supporting table and column documentation, outlier detection, and completeness metrics across all datasets within a data product. In addition, implemented a DORA KPI Databricks dashboard used across all data products. Optimized CI/CD processes in Azure DevOps to streamline deployment across development, test, and production environments.
Technology stack: Azure Databricks, PySpark, SQL, Delta Lake, Unity Catalog, Azure Data Lake, APIs, Dremio, Azure DevOps, YAML, Git, Databricks Workflows, Application Insights, Terraform, OpenAI API, Codex, LLM-assisted workflows
Gyan P.
Last position:
Senior DevOps & Cloud Architect, Head of Infrastructure at Bosch
- Azure Landing Zone architecture: Design and implement a hub-spoke, multi-region-capable Azure landing zone that provides the secure, scalable and highly available foundation for autonomous driving and parking data/ML platforms.
- Compliance through Azure Policy: Enforce security and compliance standards across Azure subscriptions via Azure Policy (guardrails, deny/audit/deploy-if-not-exists), consistently achieving top-tier infrastructure security scores.
- Infrastructure-as-Code: Automate provisioning and configuration of Azure resources with Terraform and Bicep, with changes delivered through reviewed CI/CD pipelines.
- Azure Databricks and Unity Catalog: Extensive experience operating Azure Databricks with Unity Catalog for centralized data governance, access control, lineage and auditing across workspaces.
- Monitoring and observability: Built and run infrastructure monitoring and logging with Azure Monitor, Prometheus, Grafana and Loki, covering platform health, alerting, troubleshooting and capacity trends.
- Platform at scale: Architected and operate cloud data/ML platforms supporting multi-PB vehicle data ingestion and simulation; orchestrate Argo Workflow-based recompute and autolabeling services scaling to 100k+ concurrent pods on AKS.
- Reproducible ML: Established reproducible training environments with dataset versioning and provenance tracking, enabling auditing and experiment reliability.
- Operational excellence: Automated GitHub organization management and CI/CD pipelines, improving developer productivity and deployment reliability; automated recurring operational processes.
- FinOps: Developed transparent resource utilization and cost-tracking for multi-project Azure environments.
- Leadership: Technical lead for infrastructure topics, collaborating with development, DevOps and security teams; technical interviewer and recruitment panel member for scaling the engineering team.
Ehsan M.
Last position:
BI Developer at Telecommunications Infrastructure
- Gathered and analyzed requirements in close collaboration with business departments to develop data-driven solutions and scalable PowerBI reporting infrastructures.
- Conducted detailed error analyses and optimized existing semantic and data models to ensure a robust data architecture and high data quality and to improve PowerBI reporting.
- Developed and implemented scalable ETL processes for data preparation and integration.
- Built a wiki for table and view descriptions as well as PowerBI PowerQuery and KPI documentation to ensure a consistent understanding of data structures and key performance indicators.
Olga M.
Last position:
Migration of the existing DWH from MS SQL Server to Azure Databricks at Oraylis GmbH
- Led the migration of the existing DWH, including HR data, application processes, project business and time tracking, from an MS SQL Server environment to Azure Databricks
- Refactored existing data models and ETL processes and extended them with new objects and functionalities
- Used Azure Databricks (Unity Catalog, Notebooks, Spark SQL, Databricks Dataflows) and Power BI
- Technologies: MS SQL Server 2019 (SSMS, SSIS), Power BI, Delta Lake, Azure Databricks
Anton R.
Last position:
AI-Engineer at Publicly traded company, industrial safety technology
- Designed and implemented the agent-based AI architecture for a company-wide platform to securely deploy LLM-based agents
- Designed and implemented end-to-end RAG pipelines from multiple sources: document preprocessing, chunking strategies for different document types, embeddings, retrieval with re-ranking, and robust prompt orchestration
- Developed a modular context engineering framework with skill architecture, context isolation, and dynamic resource management; human-in-the-loop control for enterprise tool integrations
- Built the CI/CD pipeline, testing strategy, tracing on the software side as well as automated LLM and agent evaluations, red team testing and tracing, and handed over to a reproducible production environment (ISO27001 and SOC2 compliant)
Marco L.
Last position:
Senior IT Consultant | Cloud Data Engineer | Infrastructure Architect at Hannover Rück SE
Built an enterprise data lakehouse platform on Azure Databricks
Developed production data pipelines and governance structures
Implemented private cloud infrastructures using Terraform
Introduced modern CI/CD standards in Azure DevOps
Implemented secure IAM and governance concepts
Developed scalable PySpark and Delta Lake frameworks
Supported self-service analytics and data product approaches
Provided architecture and platform consulting for enterprise data initiatives
Built a central DataHub architecture for insurance data
Integrated multiple subsystems into a lakehouse platform
Introduced data governance and data lineage
Supported modern analytics and reporting standards
Optimized data delivery for business and analytics teams
Nima N.
Last position:
Co founding LLM Engineer at LLM Ventures
- Co-founded an AI venture focused on building production-grade LLM applications and agentic systems
- Designed and implemented multi-agent AI workflows for financial and trading applications
- Developed LLM-powered copilot architectures for portfolio analysis, trade management, and personalized user coaching
- Built on-device and edge-deployed inference applications, optimizing models for low latency, privacy, and resource-constrained environments
- Led system architecture decisions across model selection, orchestration, state management, and deployment
Guino N.
Last position:
Senior Data Engineer at Infomotion
- Building a Data Analytics platform for Karl Storz
- Generic development of all ETL processes
- Preparing and providing data in Databricks Delta tables for reuse in Databricks Machine Learning
- Technologies & Tools: Azure Data Factory, CI/CD Pipeline with GitHub DevOps, Python, Azure Databricks (Unity Catalog), T-SQL
Vladislav L.
Last position:
Freelance Data Engineer / Architect at Deutsche Bank
Designed and implemented a scalable data lake on Google Cloud Platform (GCP) for the Anti-Financial Crime (AFC) division, supporting Anti-Money-Laundering and Counter-Terrorism-Financing initiatives
Built robust data pipelines for ingesting and processing over 30 million daily transactions from retail and corporate banking, applying dimensional modeling to enable advanced analytics and regulatory reporting
Ensured resilience by implementing change data capture, late-data handling, and schema evolution across evolving source systems
Led a small engineering team and collaborated with international stakeholders in Germany, Singapore, Sri Lanka, Hong Kong, Taiwan, and Thailand to ensure compliance, data quality, and performance
Google Cloud Platform (GCP)
Apache Spark (Dataproc & Cloudera Data Platform - Python PySpark)
Apache Airflow (Cloud Composer - Python API)
Google Cloud Storage
BigQuery
GitHub Actions
Terraform
Google Kubernetes Engine (GKE)
Leonard H.
Last position:
Freelance Software Engineer & Cloud Architect at Leonard Hußke - IT Solutions
- Evaluation of potential providers (Snowflake vs Databricks) and design of the analytics data platform using Databricks
- Data storage and ingestion layer with Amazon S3
- Creation of ETL processes and data transformations with AWS Glue and Databricks Notebooks
- Orchestration with AWS Glue Workflow, Databricks Workflow and Databricks DLT
- Processing of unstructured data, including text, images and video
- Databricks workspace setup and administration
- Implementation of a medallion architecture to ensure data quality
- Evaluation of potential BI tools (Power BI, AWS Quicksight, Tableau)
- Establishment of MLOps using MLFlow
- Introduction of data governance and data lineage using Unity Catalog
Discover over 15,000 top freelancers
Statistics of experts using Unity Catalog
Aggregated from the professional profiles of matched freelancers.
Experience
11 years
Position duration
1.8 years
Positions per freelancer
7
Top business areas
Information Technology, Business Intelligence, Product Development
Top industries
Information Technology, Banking and Finance, Manufacturing
Certification focus areas
Information Technology, Business Intelligence, Research and Development
Bachelor's degree or higher
100%
Master's degree or higher
50%
Doctorate
8%
Certifications per freelancer
4
Most common languages
German, English, Russian
Speak two or more languages
100%
Based on our profile pool as of 29 Oct 2026.
Daily rate distribution
The chart shows how the daily rates of experts in this technology in Germany 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 in Germany using Unity Catalog
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 29 Oct 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
Unity Catalog 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 (75%)
- Banking and Finance (67%)
- Manufacturing (50%)
- Retail (42%)
- Automotive (33%)
- Energy (33%)
- Professional Services (33%)
- Chemical (25%)
Please note that freelancers can work across multiple industries, so percentages overlap.
About the technology
Data governance foundation
Unity Catalog is Databricks’ unified governance layer for data and AI assets. It gives teams a central way to organize catalogs, schemas, tables, views, volumes, models, and functions across workspaces. Companies use it to apply consistent ownership, discovery, access control, and auditing without losing the flexibility of their lakehouse architecture.
Core capabilities
Unity Catalog supports fine-grained permissions, lineage, data discovery, and centralized administration. Experts configure account-level governance, workspace bindings, external locations, storage credentials, and managed or external tables. They also establish naming standards and ownership models that keep analytics environments understandable as data products grow.
- Define catalogs, schemas, and ownership rules
- Configure access with grants, groups, and service principals
- Track lineage across pipelines, queries, and models
- Govern files, volumes, functions, and machine learning assets
Databricks ecosystem
The technology works closely with Databricks SQL, Apache Spark, Delta Lake, and Delta Sharing. Effective specialists understand cloud storage, identity and access management, infrastructure as code, and the surrounding data engineering workflows. They may also connect Unity Catalog with BI tools, orchestration services, catalog integrations, and external data platforms.
When expertise matters
Companies often bring in freelance specialists during a Databricks migration, workspace consolidation, or governance redesign. Expertise is valuable when permissions are inconsistent, sensitive data lacks clear controls, lineage is incomplete, or teams need a repeatable operating model. In Germany, projects may also involve collaboration across local offices, remote teams, and international data organizations.
- Move from workspace-level controls to centralized governance
- Separate development, testing, and production access
- Prepare governance for regulated or sensitive data
- Document ownership, lineage, and operating procedures
Delivery and integration
A Unity Catalog project can include architecture decisions, tenant and workspace configuration, permission models, migration plans, automated deployment, and operational documentation. Strong professionals connect governance with real delivery processes rather than treating it as a standalone administration task. They test access paths, validate lineage, and make controls usable for analysts, data scientists, and application teams.
What strong experts bring
The best specialists combine practical Databricks knowledge with security discipline and clear communication. They can explain the effect of managed versus external data, distinguish account-level from workspace-level controls, and anticipate permission conflicts. They also leave behind maintainable configurations, tested automation, and guidance that internal teams can operate confidently.
Frequently asked questions
Curious about Unity Catalog? Here are the answers that come up again and again.
Unity Catalog provides centralized governance for data and AI assets in Databricks. Companies use it to manage access, organize catalogs and schemas, trace lineage, register models, and create a consistent control layer across workspaces.
Unity Catalog is closely integrated with the Databricks lakehouse, Delta Lake, Spark workloads, and Databricks identities. General-purpose catalog tools may cover a wider range of external systems, while Unity Catalog is often preferred when governance must operate directly inside a Databricks environment.
A strong Unity Catalog specialist usually understands Databricks administration, SQL, Apache Spark, Delta Lake, cloud storage, and identity management. Terraform, CI/CD, data classification, and experience with BI or orchestration tools can also be important for a complete implementation.
For a small configuration change, focused Unity Catalog experience may be sufficient. A migration or enterprise governance program calls for someone who has handled workspace structures, storage credentials, access models, lineage validation, automation, and operational handover in comparable environments.
Yes, much of a Unity Catalog engagement can be completed remotely through cloud consoles, infrastructure repositories, documentation, and scheduled workshops. On-site collaboration may still help when teams are redesigning operating processes, coordinating stakeholders, or working with sensitive environments in Germany.
Ask the Unity Catalog specialist to explain a permission model, managed and external data choices, workspace bindings, and a lineage validation approach. Look for clear reasoning, practical examples, careful treatment of service principals and storage access, and documentation that another team can maintain.
Unity Catalog can replace fragmented workspace permissions with a more consistent governance structure. A specialist can plan catalog and schema design, map identities and groups, address external locations, preserve useful lineage, and reduce disruption while workloads move between environments.
Unity Catalog governs more than tables and views; it can also cover models, volumes, functions, and other assets used in machine learning workflows. Specialists help teams connect model access, data permissions, lineage, and deployment controls so experimentation and production work follow the same governance principles.
The average hourly rate of freelancers in Germany who have used Unity Catalog in their recent projects is 95 €, which corresponds to a daily rate of about 760 € based on an 8-hour working day.
Of the freelancers in Germany who have used Unity Catalog in their recent projects, 100% hold at least a Bachelor's degree, 50% hold at least a Master's degree, and 8% hold a doctorate.
On average, freelancers in Germany who have used Unity Catalog in their recent projects have 11 years of professional experience, with a single engagement typically lasting around 1.8 years.
The most common languages among freelancers in Germany who have used Unity Catalog in their recent projects are German (100%), English (100%), and Russian (25%).
The most common industries among freelancers in Germany who have used Unity Catalog in their recent projects are Information Technology (75%), Banking and Finance (67%), and Manufacturing (50%).
The most common business areas among freelancers in Germany who have used Unity Catalog in their recent projects are Information Technology (100%), Business Intelligence (92%), and Product Development (75%).
Main locations of FRATCH Experts, who have recently used Unity Catalog
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 Request a free demo
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FRATCH CEO
