Philipp Müller

Pervasive Data Intelligence Data and analytics platform strategy, solution architecture

Juli 2019–today: IT Architecture and Management - Identification of potentials to meet current and future business requirements for IT management. Strategy development (analysis and description) aligned with key success factors and business mission. Jan. 2011–Juli 2019: IT Architecture and Platform Engineering - Distributed/clustered computing, massively parallel infrastructures, database technologies. Cloud-native platform development.

Lead Architect - Group Data Analytics Platform Core (GDAPc) Areas of responsibility: platform architecture, platform engineering (Kubernetes, AWS, Azure), technology evaluation (software defined storage, massive parallel processing, distributed query engines, data science life cycle support), strategic program management.

Data Platform Architecture Hybrid analytics platforms with Teradata (Apache Hadoop, and Apache Spark). Areas of responsibility: requirements engineering, data strategy, data platform architecture, technology evaluation, and information security in context of distributed and massive parallel data analytics platforms (on-premises, cloud, and hybrid solutions)

Internet of Things (IoT), Azure Stream Analytics Scalable and stable analytics solutions on Microsoft Azure. Areas of responsibility: architecture, requirements engineering, pre-sales, cloud based technology evaluation, proof of concepts.

Data architecture (based on agile and domain driven practices, advocated decisions, and design principles). Areas of responsibility: requirements engineering, data modeling, data integration, architecture of distributed and massive parallel data analytics platforms (on-premises, Hadoop [Cloudera, Hortonworks], Teradata RDBMS).

data warehouse strategy, architecture frameworks and principles, project management, requirements engineering, technology evaluation (massively parallel data processing, and hybride data warehouse solutions), and operations Industry: risk management, financial services, and scoring

Areas of responsibility: data warehouse strategy, architecture frameworks and principles, project management, requirements engineering, technology evaluation (Apache Hadoop, Apache Spark, and hybride data warehouse architecture), and operations. Industry: risk management, financial services, scoring

data warehousing, data modelling, ETL, reporting, data quality, 3rd Level Support Microsoft OS/Microsoft SQL Server, operation and system management Industry: automotive, government

IT Management (strategy, architecture, security), International Management and Intercultural Communication, Mobile Computing and Embedded Systems

Software-Engineering (C++, Java), Business Intelligence and Analytics