Berlin, Germany • +49 (0) 30 4193 6978 • inquiry@crichter.io
I am a Data Engineer with more than 15 years of experience building reliable ETL pipelines on scalable cloud infrastructure. I help organizations designing and implementing fully automated, data driven processes to support the business case using modern technology and data infrastructure. How can I help you?
I support customers in the design and implementation of cloud-based data infrastructure and data-driven process pipelines.
AltusInsight has developed the cloud-based software LambdaNow, a deployment platform for data infrastructure. I founded and run the company for 8 years.
My main focus was to enable customers using big data technologies to cater to their data processing needs.
First employee of the start-up. Worked on backend software, databases and infrastructure. Implemented algorithms to customize user experience.
Researched various algorithms on speech recognition.
Researched various algorithms for financial fraud detection.
Supply chain management consulting and implementation services.
Industry: Logistics
Technologies: Google Cloud, GKE, SQL, Kotlin, Pekko, Kafka, GitHub
Support and implementation services.
Industry: Chemistry
Technologies: AWS Cloud, Spring Boot, Java, Docker, GitLab
Concept and support of an on-premise data warehouse migration towards the cloud.
Industry: Market research
Technologies: AWS Cloud, LakeFormation, Glue, EMR, Athena, Lambda, SQS, S3, Docker, Spark, Hadoop, Airflow, Terraform, Python, GitLab
Design and implementation of a cloud-based data ware house for processing user related data.
Industry: Entertainment
Technologies: AWS Cloud, Kubernetes, Docker, Spark, Airflow, Kafka, Terraform, Python, Kustomize, GitLab
Design of AWS managed infrastructure platform for sensor data processing, extension of an existing data science environment.
Industry: Consumer Goods
Technologies: AWS Cloud, Kubernetes, Kafka, Spark, Bamboo, Java, Docker, Terraform
Design and implementation of a cloud-based data warehouse for evaluation of vehicle data. Design and implementation of a data science environment.
Industry: Automotive
Technologies: AWS Cloud, Lambda, IAM, Airflow, Kubernetes, Terraform, Python, Jenkins
Design and implementation of a cloud-based data warehouse & data science environment.
Industry: Consumer Goods
Technologies: AWS Cloud, Kubernetes, Spark, R, NiFi, Terraform, Docker, Jupyter NB
Support conception and implementation/migration of a monolith into a micro service architecture.
Industry: Financial services
Technologies: Micro Services, Java, Docker, Kafka, Liquibase, Jenkins
Support in evaluating big data providers
Industry: Energy
Technologies: Hortonworks, Cloudera, SAP Cloud, Apache NiFi, AWS Cloud, MS Azure, Terraform
Design and implementation of a cloud-based big data warehouse in the AWS Cloud for market research analytics.
Industry: Market research
Technologies: Spark, SparkR, Hadoop, Hive, Jupyter, AWS Cloud, R, Bamboo, Terraform
Workshop Big Data Technologies - Introduction and Getting Started.
Industry: Education
Technologies: Hadoop, Spark, AWS Cloud, MapReduce, Hive, Pig, R, Terraform
Architecture review and design and implementation of a realtime aggregator for machine statistics.
Industry: Entertainment
Technologies: Hadoop, Spark, AWS Cloud, Scala, MapReduce, JCascalog, RedShift
Support in the development of ETL processes on a Hadoop based DWH.
Industry: Online retail
Technologies: Hadoop, Hive, Spark, Redis, Kafka, Avro, Scala, HCatalog, Schedoscope
Design and implementation of a continuous deployment & delivery pipeline for data-driven applications in cloud environments.
Industry: Market research
Technologies: AWS Cloud, Hadoop, Spark, Bamboo, Git, Terraform, Vagrant, InfluxDB
Conception and implementation of a data ware house based on big data technologies - OLAP workload.
Industry: Technology
Technologies: Hadoop, Impala, Hive, ETL, AWS Cloud
Design and implementation of a big data system for batch and real-time data processing of machine generated data.
Industry: Consumer Goods
Technologies: Hadoop, Samza, Spark, Kafka, Java, ETL, AWS
Design and implementation of Hadoop based data warehouse for online game analytics.
Industry: Entertainment
Technologies: Hadoop, Map / Reduce, Kafka, Hive, ETL, Java, Linux
Design and implementation of a big data infrastructure in virtualized environments.
Industry: Telecommunication
Technologies: Hadoop, OpenStack, Opscode Chef, Java, Linux
Design and implementation of a big data architecture for evaluating telecommunications data.
Industry: Market research
Technologies: Apache Hadoop, Hive, Flume, Java, Spring, Puppet, Ubuntu Linux, AWS
I thrive on building new things from scratch, contributing best practices from previous projects and experience on how to design, build, deploy and operate data processing software and infrastructure.
Understanding customer needs and business requirements and translating them into infrastructure and software is one of my core competency used throughout the lifetime of every project. My focus on the essential core value proposition provides value to the customer early on.
I support and enable teams to efficiently build and operate data-driven processes. Sharing knowledge and best practices on designing and implementing reliable ETL processes and required infrastructure components is part of my daily routine.
Having worked on more than 20 projects allowed me to learn and use a broad variety of tools and services to design and build data-driven backend processes. This understanding helps me in choosing the right tools and technologies for the task given.
"Chistian's expertise with distributed and AWS based infrastructures helped us big time when we needed a solution to orchestrate our servers and services, by integrating Terraform into our application lifecycle management."
"Thanks to the use of big data technologies for our tracking backend, we are now able to analyze the behavior of our users much more precisely and to significantly improve the game play of our games."
I support your organization to design and develop a data strategy that aligns with the business goals and organizational structure and provide guidance in the design and implementation of ETL processes and required cloud infrastructure.
If you are planning a new project and need help getting started I'm ready to support you and your team. After drafting an initial concept based on the business requirements, I immediately start setting up cloud infrastructure, CI/CD pipelines and ETL processes.
I help you to improve the performance of an application by reviewing the architecture and identifying weak spots (e.g. how data is partitioned, stored and processed) and provide suggestions for remediation.
I offer various workshops touching data engineering topics and cloud infrastructure best practices. Don't hesitate to get in touch to learn more about my workshop offerings.