About the Role

Swiss Himmel GmbH is seeking a highly experienced Principal Data Modernization Architect to lead large-scale enterprise data transformation and modernization initiatives within a complex, regulated environment.

This is a senior technical leadership role for an expert who can design and deliver end-to-end data migration, transformation, and automation frameworks across cloud, hybrid, and legacy ecosystems. You will combine deep Python engineering, Azure data architecture, legacy platform modernization, and machine learning engineering to build intelligent, scalable, and secure enterprise data platforms.

You will operate as a Subject Matter Expert (SME) and trusted advisor, guiding architecture strategy, developing migration accelerators, and leading engineering teams through highly complex cross-platform transformations.

Your Responsibilities

• Lead the design and delivery of enterprise-wide data modernization strategies and architectures
• Architect metadata-driven migration frameworks using Python to automate schema discovery, transformation, reconciliation, and validation
• Design scalable ETL/ELT platforms supporting multi-terabyte datasets and heterogeneous systems
• Establish engineering standards, governance models, and reusable modernization toolkits
• Drive end-to-end cloud and legacy platform integrations across hybrid environments
• Provide technical leadership and mentorship to engineering teams across architecture, development, and deployment phases
• Collaborate with enterprise architects, security, and business stakeholders to align technical delivery with strategic goals

Azure Data Platform Engineering

Design and implement advanced solutions using:

• Azure SQL Database
• Azure SQL Ledger Tables
• Azure Data Factory (ADF)
• Azure Functions
• Azure Storage
• Azure Authentication (Managed Identity, OAuth, MSAL)

Build secure, high-throughput data ingestion, orchestration, and monitoring pipelines. Implement lineage, observability, and compliance mechanisms across the Azure data ecosystem.

Legacy System Modernization & Migration

• Lead complex migrations from Mainframe DB2, Oracle, and AS400 environments
• Reverse engineer legacy schemas, business rules, and COBOL-based systems
• Utilize SSMA for schema conversion and automated validation
• Ensure end-to-end data integrity and reconciliation using cryptographic validation techniques
• Develop automated validation, lineage tracking, and migration assurance frameworks

API, DevOps & Automation

• Develop API-driven orchestration workflows using Control-M (Ctrl-M)
• Implement GitLab-based CI/CD pipelines and Ansible-driven infrastructure automation
• Apply DevOps best practices, testing frameworks, and infrastructure-as-code approaches
• Lead Python-based engineering and development using Visual Studio Code

Machine Learning Engineering

• Design, train, and deploy models using PyTorch, TensorFlow, and scikit-learn
• Embed ML-driven intelligence into ETL and migration frameworks, including:
  • Data quality scoring
  • Anomaly detection
  • Schema drift detection
  • Predictive migration planning
• Operationalize ML components within Azure-native architectures

Your Profile

• 20+ years of experience in enterprise data engineering, ETL, and large-scale migrations
• Expert-level Python engineering and automation framework development
• Mandatory machine learning engineering expertise
• Deep experience with Azure data services and cloud-native architectures
• Proven experience modernizing legacy mainframe and enterprise database platforms
• Strong knowledge of API engineering, CI/CD, and DevOps automation practices
• Experience designing large, reusable ETL and migration toolkits
• Excellent stakeholder management and leadership capabilities
• Experience working in regulated or compliance-driven environments

What We Offer

• Opportunity to lead high-impact enterprise modernization programs
• Strategic, senior-level architecture role with strong ownership
• Complex, cutting-edge technology landscape across cloud and legacy platforms
• Long-term, stable engagement within Switzerland
• Collaborative, expert-level engineering environment