As a Data Architect, you are required to:
Design & develop technical solutions which combine disparate information  to create meaningful insights for business, using Big-data architectures
Build and analyze large, structured and unstructured databases based on scalable cloud infrastructuresDevelop prototypes and proof of concepts using multiple data-sources and big-data technologiesProcess, manage, extract and cleanse data to apply Data Analytics in a meaningful wayDesign and develop scalable end-to-end data pipelines for batch and stream processingRegularly scan the Data Analytics landscape to stay up to date with latest technologies, techniques, tools and methods in this fieldStay curious and enthusiastic about using related technologies to solve problems and enthuse others to see the benefit in business domainQualification: Bachelor's or Master's in Computer Science & Engineering, or equivalent. Professional Degree in Data Engineering / Analytics is desirable.Experience level: Minimum 8 years in software development with at least 2 - 3 years hands-on experience in the area of Big-data / Data Engineering.Desired Knowledge & Experience:Data Engineer - Big Data DeveloperSpark: Spark 3.x, RDD/DataFrames/SQL, Batch/Structured StreamingKnowing Spark internals: Catalyst/Tungsten/PhotonDatabricks: Workflows, SQL Warehouses/Endpoints, DLT, Pipelines, Unity, AutoloaderIDE: IntelliJ/Pycharm, Git, Azure Devops, Github CopilotTest: pytest, Great ExpectationsCI/CD Yaml Azure Pipelines, Continuous Delivery, Acceptance TestingBig Data Design: Lakehouse/Medallion Architecture, Parquet/Delta, Partitioning, Distribution, Data Skew, CompactionLanguages: Python/Functional Programming (FP)SQL: TSQL/Spark SQL/HiveQLStorage: Data Lake and Big Data Storage DesignAdditionally it is helpful to know basics of:Data Pipelines: ADF/Synapse Pipelines/Oozie/AirflowLanguages: Scala, JavaNoSQL: Cosmos, Mongo, CassandraCubes: SSAS (ROLAP, HOLAP, MOLAP), AAS, Tabular ModelSQL Server: TSQL, Stored ProceduresHadoop: HDInsight/MapReduce/HDFS/YARN/Oozie/Hive/HBase/Ambari/Ranger/Atlas/KafkaData Catalog: Azure Purview, Apache Atlas, InformaticaBig Data ArchitectExpert: in technologies, languages and methodologies mentioned in Data Engineer - Big Data DeveloperMentor: mentors/educates Developers in technologies, languages and methodologies mentioned in Data Engineer - Big Data DeveloperArchitecture Styles: Lakehouse, Lambda, Kappa, Delta, Data Lake, Data Mesh, Data Fabric, Data Warehouses (e.g. Data Vault)Application Architecture: Microservices, NoSql, Kubernetes, Cloud-nativeExperience: Many years of experience with all kinds of technology in the evolution of data platforms (Data Warehouse -> Hadoop -> Big Data -> Cloud -> Data Mesh)Certification: Architect certification (e.g. Siemens Certified Software Architect or iSAQB CPSA)Required Soft-skills & Other Capabilities:
Excellent communication skills, in order to explain your work to people who don't understand the mechanics behind data analysisGreat attention to detail and the ability to solve complex business problemsDrive and the resilience to try new ideas, if the first ones don't workGood planning and organizational skillsCollaborative approach to sharing ideas and finding solutionsAbility to work independently and also in a global team environment.