Senior Data Engineer — Scalable Data Platforms (Hybrid)

Tieto; Graz; Hybrid; EUR 40,000 - 48,000; Full time

Benefits offered by this job

Hybrid work model

Health programs

Public transport access

Food vouchers

Job summary

Tieto Tech Consulting seeks a Senior Data Engineer in Austria to design and build scalable data platforms. You will develop data pipelines using Databricks or similar tools, implement governance, and optimize CI/CD deployments.

You will collaborate with stakeholders to deliver impactful data-driven solutions while ensuring performance and reliability across data workflows. Ideal candidates have 5+ years in data engineering, strong data modeling, and proficiency in Python and SQL, with fluency in

Qualifications

• 5+ years of experience in designing and implementing scalable data solutions.
• Strong data modeling skills (dimensional, normalization/denormalization).
• Proven experience with cloud-based data platforms (Azure preferred; AWS/GCP welcome).
• Proficient in Python and SQL with an interest in AI-assisted stakeholders.
• Ability to communicate complex concepts to technical and non-technical stakeholders.

Responsibilities

• Design, build, and maintain scalable data platforms and governance structures.
• Develop robust data pipelines using Databricks or similar frameworks.
• Manage CI/CD pipelines, containerization, and orchestration for deployments.
• Act as trusted technical advisor for customers and cross-functional teams.
• Collaborate to deliver data-driven solutions and monitor performance.

Skills

Python

SQL

Data modeling

Cloud platforms

German C1

English

Consulting mindset

Ownership

Tools

Databricks

Microsoft Fabric

Git

CI/CD pipelines

Job description

Tieto Tech Consulting seeks a Senior Data Engineer in Austria to design and build scalable data platforms. You will develop data pipelines using Databricks or similar tools, implement governance, and optimize CI/CD deployments.

You will collaborate with stakeholders to deliver impactful data-driven solutions while ensuring performance and reliability across data workflows. Ideal candidates have 5+ years in data engineering, strong data modeling, and proficiency in Python and SQL, with fluency in