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# Technical Data Analyst

- **Company:** ITC GmbH
- **Location:** Stuttgart, Germany
- **Experience:** Expert
- **Salary:** €60,000.0 - €65,000.0
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Microsoft Azure, Data Validation, Information Engineering, Data Mapping, Data Migration, Data Structures, Data Systems, Data Warehousing, Dimensional Modeling, Document-Oriented Databases, Logical Data Models, Oracle Databases, Oracle (Applications), Cloud Services, Standard Sql, SQL Databases, Data Streaming, Enterprise Data Management, Data Processing, Azure Data Factory, Data Lineage, Data Analytics, Star Schema, Data Management, Physical Data Models, Azure Synapse Analytics, Databricks
- **Published:** September 18, 2026
- **Apply:** https://www.jobfinder.de/job/data-analyst-w-m-d/

## About the Role

mappings, business rules, transformation logic, data lineage, and data flows. Work with Azure-based data platforms and Databricks environments to support analytics and migration initiatives. Facilitate stakeholder discussions and explain technical concepts to business users. Required Skills & Qualifications 5-10 years of experience in Data Analysis, SQL, Technical Business Analysis, or Techno-Functional Data roles. Experience working across business and technical teams in data-driven environments. SQL & Data Analysis Strong SQL with hands-on querying experience. Experience in Oracle databases and complex data analysis. Ability to perform data validation, reconciliation, and root-cause analysis. Data Modelling Strong understanding of Data Modelling concepts. Hands-on experience with: Conceptual Data Models Logical Data Models Dimensional Modelling (Star/Snowflake Schemas) Data Warehouse Design Principles Experience validating and collaborating on enterprise data models. Data Migration &
Mapping Source-to-Target Mapping (STTM) experience. Experience in at least one end-to-end data migration project. Understanding of data lineage, transformation rules, and data quality validation. Cloud Data Platforms Experience working with Microsoft Azure data technologies such as: Azure Data Factory Azure Synapse Analytics Azure Storage / ADLS Experience with Databricks, including: Databricks SQL Data processing and validation Collaboration with Data Engineering teams Business & Stakeholder Management Ability to translate business requirements into technical specifications. Experience collaborating with business stakeholders, data modelers, and engineering teams. Strong communication and documentation skills. Preferred Domain Experience Supply Chain (Manufacturing) - Highly Preferred Inventory Management Procurement Warehouse Management Logistics Order Management Manufacturing Operations Our X-Factor Work ethic: You are a consummate professional. Aptitude: You have an innate capacity
to transition from project to project without skipping a beat. Communication: You have excellent written and verbal communication skills for coordination across projects and teams. Impact: You are a critical thinker with an emphasis on creativity and innovation. Passion: You have the drive to succeed paired with a continuous hunger to learn. Leadership: You are trusted, empathetic, accountable, and empower others around you. Tid-2

## Description

technical-first, not coding-heavy, and requires strong communication and stakeholder management skills. The ideal candidate should have hands-on experience working with enterprise data platforms, data migration initiatives, and modern cloud data ecosystems such as Microsoft Azure and Databricks. Salary: Euros 60K-65K/Annum Gross + Bonus Working Mode: Onsite for 3days/week Key Responsibilities Perform data analysis across Oracle, Supply Chain, Manufacturing, and enterprise datasets. Develop SQL queries to extract, validate, reconcile, and analyze data. Create and maintain Source-to-Target Mapping (STTM) documents for development and migration projects. Translate business requirements into functional and technical specifications. Collaborate with Data Modelers and Data Engineering teams to validate solutions and data structures. Define, review, and validate conceptual, logical, and physical data models. Support data migration, data quality, and reconciliation activities. Document data


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