Sebastian Rama

MB.CE provide harmonized, nondomain-specific Cloud Services and processes via a managed marketplace for Mercedes-Benz One, harmonized offering for non-business differentiating problems Drive business by focusingon custom business differentiating solutionsEffective use of precious resources, Unified, frictionless experience of a platformFocus on API first, automation & self-serviceFoster a mindset of openness to integrate products of 3rd partiesEnsure the core assets (APIs, Events,Data) are available.

Motivate and enable our customers on their Enterprise Data Cloud journey Participate in the pre and post sales process, helping both the sales and product teams to interpret customer use cases Drive POCs with customers to successful completion Design and implement Enterprise Data Cloud architectures and configurations for customers Work directly with customer technical resources to devise, recommend and implement solutions based on the understood requirements

Support the Big Data platform (Spark, Hive, etc.) Linux, Kerberos, scripting with Bash & Python.DevOps approach with Git and Ansible to manage clusters Designing and building cloud-based data solutions and more specifically with AWS (IAM, S3, Glue, EMR, EKS, Sagemaker, …). NiFi: Establishing enterprise-level framework: automating intake procedure, promotion and smaller components (GitLab) Establishing monitoring and alerting solutions on cluster level with Open Source solutions.

vent Driven Architecture: Development of POC streaming: using Kafka for data messaging, Flink for data processing and mapping. +Define requirements for Event Driven Architecture using NIFI on a Cloudera Cluster. -Optimize Kafka Producer API with authentication and cluster Management -Clarified Kafka Subscriber API -Define requirements for Test Data Management -Implement common cache API +Define evaluation criteries to compare Flink and Spark Streaming with NiFi +Compare Flink and Spark Streaming

Migration of a BDR organizational model to a Data Vault modeling, developing different data collection orchestration services from operational systems that adhere to the new model made up of different geographical units, provisioning process and transformation of the same according to design specifications defined in a JSON configuration file and finally its loading in the Common Data layer (Data Lake) for its subsequent classification and control audit by the business units that receive said information.

Perform operational and Tier 3 level support for production applications in a range of business portfolios. Responsibilities involve the daily management of incidents, operational maintenance and support, development support, and proactive/preventative analysis of systems. · Analysis, troubleshooting, and diagnosis of incidents relating to off-the-shelf and proprietary applications and/or platforms. · Determination of root cause of incidents (configuration vs. defect)

Main task: Design solutions and develop with Hortonworks DataFlow (HDF) to implement a company-wide, business-critical data lake solution, working as part of a team. Experience in an enterprise Big Data solution environment. Experience with Apache Hive and Phoenix Data encryption at rest for GDPR compliance (Ranger KMS). KMS Encryption implementation Implementations at DEV/UAT/PROD using Ansible playbooks.Apache Atlas, Apache Knox, Superset, Solr Cloud, Hue. Automation and maintenance of data clusters.

-Member of the DataLake Team. -Member of the "Big Data & Analytics as a Service” project -Linux Administration (RHEL,Microinstances,etc) over PaaS and AaaS and Windows 2012 R2. -Security and AWS: Support relevant practices AWS IAM, encryption, authentication, federation and use cases and solutions. -Support the AWS architecture for high availability architectures and highly scalable, including aspects of networking, storage and VPC constructs.