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# Data Engineer - Data & AI

- **Company:** RED
- **Location:** Salzburg, Austria
- **Experience:** Experienced
- **Salary:** €33,068.0
- **Contract:** Permanent contract
- **Skills:** SAP Cloud, Artificial Intelligence, Airflow, Amazon Web Services, Data Analysis, Microsoft Azure, BigQuery, Cloud Computing, Databases, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Systems, DevOps, Python (Programming Language), SAP ERP, SAP NetWeaver Business Warehouse, SAP HANA, SQL Databases, Data Ingestion, Azure Data Factory, System Availability, Snowflake, Data Lakes, Information Technology, Data Analytics, Machine Learning Operations, Data Pipelines, Databricks
- **Published:** September 11, 2026
- **Apply:** https://www.it-career.at/application.php?aid=70500

## About the Role

University degree in IT or business administration with a focus on computer science, data science, or data engineering Fluency in English, German is beneficial At least three years of experience with analytics tools such as Azure Data Factory, Snowflake, Databricks, BigQuery, Dagster, DBT Experience with SQL and Python Architectural understanding of databases and ETL/ELT pipelines Knowledge of SAP (BW, HANA, SAC), and analytics front-end tools is beneficial Demonstrated enterprise mindset, with the ability to align data-engineering solutions with broader business strategy, architecture, governance, security, compliance, and operational requirements Experience using AI coding assistants or AI-enabled data-platform tools in a professional environment Familiarity with data science and data lake platforms on modern hyperscalers such as Azure or AWS Enthusiasm for both engineering tasks and the implementation of business requirements

## Description

In this role, you will collaborate closely with data scientists, business analysts, and solution and analytics architects to shape innovative data solutions and products while driving the implementation, testing, and support of modern data pipelines using contemporary engineering practices. By developing efficient approaches to data ingestion, preparation, integration, and operationalization, you will contribute to strong data governance and compliance standards. You will develop dynamic ELT pipelines using modern analytics engineering platforms and technologies such as Snowflake, Azure Data Factory, DBT, and Dagster, while creating data solutions that are scalable, secure, reusable, and easy to maintain. By ensuring alignment with enterprise architecture standards and best practices, you will help build a robust and future-ready data ecosystem that supports business growth and innovation.
DATA & AI ENABLEMENT

You will apply AI in ways that support business objectives while ensuring adherence to security, privacy, governance, and responsible AI principles. Working closely with AI engineers, you will help design and productionize the data foundations required for AI-powered analytics, ensuring that AI systems have access to the high-quality data, features, embeddings, metadata, and evaluation datasets needed to deliver reliable and scalable outcomes.
STAKEHOLDER MANAGEMENT

You will work closely with Data Science teams, Data Cloud Architects, and business stakeholders to establish and continuously enhance governance frameworks and processes that promote the responsible and effective use of data and technology. By building strong relationships across IT, Data, Sales, Operations, Marketing, Finance, and other business functions, you will foster alignment and collaboration across the organization. In partnership with DevOps, MLOps, and Analytics Engineers, you will help maximize data availability, reliability, and accuracy while continuously improving data quality to enable the development of innovative and impactful data products.
PROJECT MANAGEMENT

You will work closely with stakeholders to gain a deep understanding of business requirements and use cases, translating insights into effective data-driven solutions. At the same time, you will drive continuous process improvement initiatives to enhance efficiency and service delivery, while creating clear documentation and engaging presentations that facilitate knowledge sharing, alignment, and effective communication across teams.


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