Cloud Architect - Data (Azure) – Power BI Solution Expert (m/f/d)

Deutsche Telekom IT Solutions Slovakia

2d•$2,200•Remote

About The Position

The Senior Data Analytics & Data Engineering Architect is a key member of the Common Data Intelligence (CDI) Hub, responsible for designing, evolving, and governing T-Systems’ central Azure Lakehouse architecture. The role focuses on transforming traditional data warehouse landscapes into modern, cloud-native data platforms that enable enterprise-scale analytics, advanced data use cases, and governed self-service BI. The Common Data Intelligence (CDI) Hub is the central data and analytics organization responsible for defining and operating enterprise-wide data platforms and standards. The team works across business domains and international engineering units to deliver scalable, secure, and future-ready Azure-based analytics solutions.

Requirements

Have a degree in (Business) Informatics, Business Administration, or equivalent practical experience
Have senior-level experience in Data Platform / Lakehouse Architecture – Expert
Have 5+ years of hands-on experience in data engineering or data architecture roles
Have proven experience transforming traditional Data Warehouse landscapes into Lakehouse / Delta Lake architectures
Have strong architectural ownership mindset, covering design, implementation, and production readiness
Have deep hands-on experience with Azure Lakehouse technologies – Advanced to Expert
Have strong expertise in Azure Databricks, Azure Data Factory, Azure Data Lake Storage, Event Hub, Azure Synapse, and Azure Logic Apps
Have advanced skills in Delta Lake, Spark, Spark Structured Streaming, SQL, and Python
Have deep understanding of data lake storage architectures and modern data processing paradigms
Have solid knowledge of relational and multidimensional databases
Have strong experience with data warehouse modeling approaches (Kimball, Inmon, Data Vault)
Have experience designing scalable IT platforms, processes, and operating models
Have the ability to define architecture principles, standards, and best practices at enterprise level
Have experience implementing prototypes, evaluations, and reference solutions
Have strong security and compliance awareness, including handling business-critical and personal data in regulated environments
Are comfortable working in agile environments using Scrum or Kanban
Have an open, communicative working style and enjoy cross-functional collaboration
Demonstrate a solution-oriented, analytical, and structured mindset

Nice To Haves

Experience with Reporting, Analytics, and Dashboarding solutions
Hands-on experience with Power BI development
Exposure to Microsoft Power Platform (Power Automate, Power Apps)
Azure certifications such as: DP-203 (Data Engineering on Microsoft Azure), DP-900 (Azure Data Fundamentals), AZ-900 (Azure Fundamentals), AI-900 (Azure AI Fundamentals), DP-100 / DP-300 / DP-420
Experience working in large, international enterprise data & analytics organizations

Responsibilities

Design and evolve the enterprise Azure Lakehouse architecture, ensuring scalability, performance, and long-term sustainability.
Lead the transformation of classic Data Warehouse environments into modern Lakehouse and Delta Lake-based architectures.
Take architectural ownership from concept through implementation, production rollout, and continuous optimization.
Define and implement architecture principles, standards, patterns, and best practices for data engineering and analytics platforms.
Design and oversee data ingestion, processing, and streaming pipelines using Azure Databricks, Azure Data Factory, Event Hub, and Azure Logic Apps.
Build and optimize data processing solutions using Delta Lake, Spark, Spark Structured Streaming, SQL, and Python.
Define data modeling strategies across data lake and warehouse layers, applying Kimball, Inmon, and Data Vault methodologies.
Collaborate with engineering teams to implement reference architectures, prototypes, and proof-of-concepts.
Enable and coach data engineering teams toward autonomous, high-quality solution development.
Ensure platform designs comply with enterprise security, data protection, and regulatory requirements.
Support advanced analytics, self-service BI, and reporting use cases across the organization.
Work closely with product owners, architects, governance, and business stakeholders in agile delivery environments.
Contribute to continuous improvement of platform architecture, development processes, and operating models.