Level: Experienced

Job Field: BI, Data

Employment Type: Full Time

Contract Type: Permanent employment

Salary: 3.724 to 4.346€ Gross/Month

Location: Linz

Working Model: Hybrid, Onsite

Job Summary

In this role, you will develop data pipelines and build robust storage solutions to prepare data for analysis and AI initiatives, ensuring that data is reliable and of high quality.

Job Technologies

Your role in the team

We are seeking a skilled and detail-oriented Data Engineer to join our growing team.
In this role, you will be responsible for designing, building, and maintaining the systems that collect, store, and prepare data for analysis across the organization.
Your work will serve as the foundation for our data-driven decision-making and AI initiatives, making you a key enabler for our analytics and AI teams.
Design and implement effective data models and table structures across various storage systems, including relational databases, NoSQL stores, data warehouses, and data lakes.
Build, maintain, and optimize robust data pipelines (ETL/ELT) to ingest, transform, and load data from production systems and external sources.
Use workflow orchestration tools to schedule, automate, and monitor data pipelines, ensuring their reliability and performance.
Define and implement data quality standards and processes (e.g., bronze, silver, gold tiering), including handling missing values and ensuring data integrity, accuracy, and completeness.
Establish and enforce data governance policies and procedures, manage data lineage and metadata, implement access controls and encryption, and support compliance with data privacy regulations (e.g., GDPR, CCPA).
Implement and manage scalable data platforms (data warehouses, data lakes) to support efficient analytics, feature engineering, and model training for AI applications.
Conduct statistical analyses and evaluations of datasets, and develop dashboards or monitoring systems to track pipeline health and data quality metrics.
Collaborate closely with AI Engineers, AI Software Engineers, QA Engineers, and Data Analysts to understand data requirements and deliver reliable, high-quality data solutions.

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Our expectations of you

Qualifications

Strong proficiency in SQL and Python for data manipulation, automation, and pipeline development.
Vertrautheit mit Big Data Tools und Frameworks wie Apache Spark, Kafka oder Hadoop.
Solid understanding of data modeling, ETL/ELT development, and data warehousing concepts.
Proficiency with version control systems (e.g., Git).
Excellent problem-solving skills and high attention to detail.

Experience

Proven experience as a Data Engineer, including designing and building data pipelines and infrastructure.
Hands-on experience with cloud platforms (e.g., GCP, Azure) and their respective data services (e.g., BigQuery, Azure Data Factory, Databricks).
Experience with data quality management and data governance principles.

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