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

Deutsche Telekom IT Solutions Slovakia
Remote

About The Position

We are hiring a senior technical expert responsible for the design and implementation of an assigned technology. The Cloud 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

  • Degree in (Business) Informatics, Business Administration, or equivalent practical experience.
  • Senior-level experience in Data Platform / Lakehouse Architecture – Expert.
  • 5+ years of hands-on experience in data engineering or data architecture roles.
  • Proven experience transforming traditional Data Warehouse landscapes into Lakehouse / Delta Lake architectures.
  • Strong architectural ownership mindset, covering design, implementation, and production readiness.
  • Deep hands-on experience with Azure Lakehouse technologies – Advanced to Expert.
  • Strong expertise in Azure Databricks, Azure Data Factory, Azure Data Lake Storage, Event Hub, Azure Synapse, and Azure Logic Apps.
  • Advanced skills in Delta Lake, Spark, Spark Structured Streaming, SQL, and Python.
  • Deep understanding of data lake storage architectures and modern data processing paradigms.
  • Solid knowledge of relational and multidimensional databases.
  • Strong experience with data warehouse modeling approaches (Kimball, Inmon, Data Vault).
  • Experience designing scalable IT platforms, processes, and operating models.
  • Ability to define architecture principles, standards, and best practices at enterprise level.
  • Experience implementing prototypes, evaluations, and reference solutions.
  • Strong security and compliance awareness, including handling business-critical and personal data in regulated environments.
  • Comfortable working in agile environments using Scrum or Kanban.
  • Open, communicative working style and enjoy cross-functional collaboration.
  • 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.

Benefits

  • Attractive and extensive work-life balance portfolio
  • Over 25 different benefits to improve personal and professional life
  • Financial benefits
  • Benefits with focus on learning and development
  • Benefits with focus on health and sport
  • Benefits with focus on family and work – life balance
  • Other benefits
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