Role and Responsibility
- Manage full lifecycle of Big Data solutions and platforms within the enterprise incl. requirements analysis, technical architecture design, application development, testing and deployment.
- Define common business and development processes and Standard Operating Environment (SOE) incl. technology platform(s), databases and tools for data acquisition, storage, transformation, analysis, etc.
- Manage corporate big data project portfolio. Develop roadmaps and implementation strategy for data science initiatives incl. Artificial Intelligence, predictive modeling and machine learning.
- Interface and collaborate with global and local IT teams incl. cloud architect(s), DevOps resources, data scientist(s) and others to form, deliver, support and continuously improve digital ecosystem and integrated platforms.
- Create technical requirements specification (especially for data scientist), documentation of processes, solutions and operating procedures.
- Work with technical and functional users and business owners to understand requirements and identify solution blocks.
- Design and provide overall end - to - end testing environment and provision sandboxes to enable data analytics practice.
- Architect and implement conceptual, logical and physical data models and blueprints. Define data formats with focus on solutions for shop floor / production context across all facilities.
- Conduct data extraction / acquisition from machines and industry solutions. Prepare and consolidate data from multiple sources to drive and enable modeling and analysis. Ensure data readiness for data scientist processing / usage.
- Drive data synchronization and guarantee consistent data quality between edge / data collection infrastructure and cloud platforms.
- Select fit - for - purpose solutions and hybrid technology delivery based on detailed cost and requirements analysis with special focus on optimization of cloud expenditure.
Qualifications, Skills and Experience
- Overall experience as Big Data Architect.
- Has worked in a global environment and cross - functional teams.
- Experience with design and deployment of high - available technology, data clusters, data lakes for large amounts of data originating from multiple sources.
- Knowledge of enterprise data management technologies including Data Warehouses, ETL tools, SQL and master data management solutions.
- Strong understanding of scalable cloud architectures with focus on Iaas and PaaS solutions especially Microsoft and Amazon IoT platforms and product portfolio.
- Experience with visualization and reporting technologies (incl. QuickSight and PowerBI).
- Strong experience in programming languages such as: C#.NET, Elastic, all types of Javascript frameworks, Python.
- Knowledge of big data tools: Hadoop, Spark, Kafka, Data Bricks
- Experience with stream - processing systems: Storm, Spark - Streaming, Azure Stream Analytics, Amazon IoT Analytics.
- Experience with a broad range of databases: MongoDB, NoSQL, Cassandra, Microsoft Datalake Gen2, Cosmos DB.
Certifications
- Amazon AWS Certified Big Data
- Microsoft Certified Solutions Expert: Data Management and Analytics
- Cloudera Certified Associate / Professional