Module Leader for a Big Data & AWS Cloud (customer BMW, München) a heavy data driven automotive project handling thousands of prototype vehicle's data, some with several TBs of new data per day, a total of more than 500 TB of data and increasing fast)

• Owning and overseeing all technical aspects (architecture, development, operations, DevOps, testing) of the Big Data project (automotive) with the recent shift on using the AWS Cloud for the data processing / scalable capabilities / lower and predictive costs
• Leading all customer meetings, owning the architecture, future plans (envisioning how the newly cloud migrated project could accommodate 20x more data than it is currently ingesting daily, while still being able to execute a lot more queries, a nice and responsive UI frontend, reducing costs, optimizing existing data processing, ? while offering parts of the processed data to other departments to consume)
• Technical management of internal and external resources, interviewing and hiring all new colleagues

Technologies:

• (starting with) an on-premises Big Data multi-tenant environment (Hadoop - BMW's CNBDP heavily customized Hadoop)
• then migrated the entire data alongside the Big Data functionality to AWS Cloud (end date ~June 2021), while continuously working on envisioning the roadmap and future additions, the entire module future path and owning the entire architecture (Big Data & AI/ML on Cloud / Hybrid Cloud), working with a growing team to transform the business requirements into ideas and then into really working software scalable solutions
• final stable Big Data landscape (AWS EMR - Spark, Scala, StepFunctions / S3 / Athena / Glue / ? ), Fancy UI (Angular JS, serverless REST APIs / API Gateway & AWS Lambda etc.), Security (all services related to high security needs of our very demanding customer)

• Overseeing the technical aspect of internal and external projects Consulting and guiding client companies' management level in all aspects related to Big Data / Data Analytics /
• Cloud computing / and for Industry: Smart Retail (IoT, Smart Data, Edge & Fog computing / ML & AI - architecture parts)
• Technical management of internal consultants and/or clients' employees involved in HCDA projects
• Creating lots of presentations, technology examples and architecture diagrams, in-house quick demos (with some extensions for purposes like: exhibitions and presentations during customer's meetings etc.)
• Establishing architecture, deciding on AWS features to be used Evaluating, planning and managing several project aspects: analytics support & Data Lake features (data governance, data security features, data processing?)
• Leading the on-site work (with colleagues or client's employees)

Technologies:

• anything matching client's in-place functionality bricks, ready to be placed or even future additions (Big Data & AI/ML on Cloud / on-premises / Hybrid or Multi Cloud)

• In charge of all architecture aspects for DIH, an upcoming product (Data Intelligence Hub ? a new data marketplace platform) built around: Big Data and real time data (eg. IoT devices), Azure (later also AWS) Cloud, strict level Security and compliance
• Also played a range of sub-roles like: Technical Leader for development team / Senior Big Data Architect / the Company's technical connection to Fraunhofer's IDS (technical discussions, workshops and direct contributions)
• Worked with more than 10 various technical experts and architects to combine their experiences into a complex solution architecture for DIH, Lead in the same time the Development group (25+ developers on various teams)

Technologies:

• Cloud agnostic Data Intelligence Hub Platform - DIH (deployed on Azure for the start and planning for easy migration toward AWS, also GCP eventually)
• Hadoop (Cloudera Altus), platform building (programmatic resources creation / maintaining)

• Playing active role into Big Data projects (2 major clients in Frankfurt and Munich)
• Establishing architecture, deciding on AWS features to be used Evaluating, planning and managing several project aspects: analytics support & Data Lake features (data governance, data security features, data processing?)
• Leading the on-site work (with colleagues or client's employees)

Technologies:

• Hadoop stack (Spark / Scala, Python, HIVE, NiFi, HBase?) using HDP / HDF (Hortonworks) on AWS cloud (AWS, massive datasets in S3)

• Playing active role into Big Data projects client acquisition, presenting clients how Big Data solutions can help their business (understanding their struggles and offering solutions, offering RfPs and technical support for on-going Big Data projects) 
• Internal networking, connecting with the existing Big Data experts from inside the company (CoE), getting to know about the Cognizant Big Data solutions and success stories details for many customers, data security, governance, analytics 
• On-site work with Cognizant colleagues or client's employees

Technologies:

• (either Cloudera, Hortonworks, MapR) on premises or 
• cloud (Azure HDInsight, AWS EMR and other connected technologies, Scala, Java, Python)

• Led a team of 4-8 developers during the Sales Dashboard implementation (offloading the Oracle
• DWHs processing to a new standalone Hadoop Cluster used just for the Seller Central Analytics team) and while revamping the whole set of Business Reports (complex analytical reports for sellers) to use the same cluster, offloading the Oracle DWH and significantly reducing costs (estimated total saving of $1M+ yearly), performing at scale, reliable and much faster than the previous non-Big Data solutions (while also allowing for many new use-cases and complex features which were not possible in older versions)
• Designed the processing flows, identified the faster storage solutions (HBase, DynamoDB, S3), performed benchmarks and Proof of Concepts, imagined architecture options and drove the technical discussions; acted as key-contact person toward management upper layer
• This solution was reused later to create a sort of Reporting Marketplace as a Service to accommodate other team's data and their business report needs

• Led the development efforts / Managed multiple teams of engineers
• Designed the software solution architecture, high and low level design documents for various projects and feature additions
• Drove all technical discussions related to our team software applications