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# Manufacturing Data Analyst

- **Company:** Almetra
- **Location:** Berlin, Germany
- **Experience:** Experienced
- **Salary:** €50,000.0 - €65,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Code Reuse, Supervisory Control and Data Acquisition (SCADA), Python (Programming Language), Operational Databases, SQL Databases, Technical Data Management Systems, Data Processing, Backend, Process Control Systems, Data Analytics, Feature Extraction, Software Coding, Industrial Software, Data Pipelines
- **Published:** July 2, 2026
- **Apply:** https://de.indeed.com/viewjob?jk=a7e44e92d951afbd

## About the Role

* 3-5 years in data analytics or process optimisation, ideally in manufacturing, automotive, pharma or other high-volume industries
 * Strong in SQL and Python (or similar) - able to write clean, efficient, reusable code
 * Experienced working with production data, sensors, or process control systems
 * Analytical mindset with understanding of data modelling, feature extraction and algorithmic thinking
 * Comfortable communicating findings to both technical and operational stakeholders
 * Curious, structured and pragmatic - you solve real problems, not just analyse them

Nice to have

 * Background in process engineering, lean manufacturing, or industrial analytics
 * Familiarity with manufacturing software (MES, ERP, SCADA, etc.)
 * Experience integrating analytics into customer-facing workflows

## Description

We're looking for a Manufacturing Data Analyst who combines solid analytical and coding skills with a strong understanding of industrial operations. You'll work directly with customers and internal teams to translate manufacturing data into actionable insights - improving both customer outcomes and our AI analytics platform.

What you'll do

 * Collaborate with manufacturing customers to analyse production data and uncover performance drivers
 * Work closely with AI and backend engineers to define, test and refine data pipelines, features and quality metrics
 * Build clear, reliable dashboards and reports that highlight process efficiency, bottlenecks and improvement areas
 * Identify anomalies or optimisation opportunities that feed back into our product's analytics layer
 * Write clean, well-structured code for data processing and analysis - maintainable, reviewable, and production-aware
 * Act as the bridge between Customer Success, Product and Engineering - turning operational insights into measurable impact


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