Jorge Machado - Data Architect

Q: Where is Jorge based?

Jorge is based in Würzburg, Germany .

Q: What languages does Jorge speak?

Jorge speaks the following languages: German (Advanced), English (Advanced) .

Q: How many years of experience does Jorge have?

Jorge has at least 7 years of experience. During this time, Jorge has worked in at least 10 different roles and for 11 different companies . The average length of individual experience is 1 year and 7 months . Note that Jorge may not have shared all experience and actually has more experience.

Q: What is Jorge's latest experience?

Jorge's most recent position is Data Architect at Deutsche Bahn .

Q: What companies has Jorge worked for in recent years?

In recent years, Jorge has worked for Deutsche Bahn , SAP AG , s.Oliver GmbH , ias Gruppe , and S.Oliver GmbH .

Q: Which industries is Jorge most experienced in?

Jorge is most experienced in industries like Transportation and Logistics , Information Technology (IT) , and Fashion and Apparel . Jorge also has some experience in Retail , Media, Entertainment and Publishing , and Insurance .

Q: Which business areas is Jorge most experienced in?

Jorge is most experienced in business areas like Information Technology (IT) , Business Intelligence , and Product Development .

Q: Which industries has Jorge worked in recently?

Jorge has recently worked in industries like Transportation and Logistics , Information Technology (IT) , and Fashion and Apparel .

Q: Which business areas has Jorge worked in recently?

Jorge has recently worked in business areas like Information Technology (IT) and Business Intelligence .

Recommended expert

Würzburg, Germany

Experience

Mar 2025 - Present

1 year

Data Architect

Deutsche Bahn

Design and provide best practices on data modeling for dbt, including changing dimensions, late arriving data handling, and testing
Design the ingestion flow from other systems into S3 and Redshift
Design and implement new partitions for Dagster and incremental loading with dbt
Map business requirements to technical architectures
Instruct junior team members

Sep 2024 - Mar 2025

7 months

Data Architect Expert

SAP AG

Led the architectural design and implementation of Kafka Tiered Storage rollout across 30+ Kubernetes clusters in multi-cloud environments (Azure, AWS, GCP)
Defined and implemented infrastructure provisioning using Crossplane for declarative and consistent deployment across cloud providers
Developed a custom Golang-based Kafka Operator to standardize tiered storage activation for data pipelines
Designed and automated GitOps-based deployment strategies using Flux and Helm for safe and repeatable rollouts
Optimized Gardener shoot configurations to align cluster resources with Kafka workload and cost efficiency requirements

May 2024 - Nov 2024

7 months

Data Architect Expert

s.Oliver GmbH

Designed a medallion architecture on Databricks for scalable, modular data ingestion, transformation, and consumption
Implemented incremental ETL pipelines using PySpark to efficiently extract and process SAP data
Architected and implemented dbt-based semantic layers with dimensional modeling for fact and dimension tables
Established Dev-to-Prod CI/CD pipelines to standardize deployment and enforce governance
Defined role-based access control and security concepts aligned with enterprise Azure standards
Enabled real-time data integration by connecting Kafka streams to Databricks for enriched analytics
Introduced AI/ML use cases, including FP-Growth for basket analysis and time series forecasting models
Mentored junior developers on Databricks best practices to ensure long-term platform adoption

Jan 2023 - Aug 2023

8 months

Data Architect Expert

ias Gruppe

Architected an end-to-end Azure Data Lakehouse solution leveraging Azure Synapse, Delta Lake, and Azure Data Lake Storage Gen2 for scalable storage and query performance
Designed and implemented streaming ingestion pipelines using Azure IoT Hub, Event Hub, and Service Bus for real-time telemetry data capture from thousands of IoT devices
Developed data integration and transformation flows using Airbyte for ELT and dbt for business logic modeling, dimensional design, and lineage tracking
Orchestrated complex data workflows using Azure Data Factory, integrating batch and streaming processes
Implemented Delta Lake-based time travel and ACID transactions for data reliability and traceability
Designed RBAC, resource tagging strategies, and monitoring with Azure Monitor and Log Analytics for operational transparency and security
Enabled Power BI integration for near real-time business dashboards and collaborated with product and operations teams on requirements translation

Sep 2022 - May 2024

1 year 9 months

Frankfurt, Germany

Data Architect Expert

Deutsche Bahn

Designed and implemented real-time streaming architectures using AWS Kinesis, Lambda, and Apache Spark for time-sensitive analytics use cases
Architected delta ingestion pipelines on AWS Glue and Apache Hudi for efficient small-file compaction and time travel analytics
Delivered business-critical KPIs and dashboards with end-to-end data lineage and auditability across S3, PostgreSQL, and CloudWatch
Defined and enforced infrastructure-as-code principles using AWS CDK for scalable, replicable environments
Introduced and rolled out dbt for semantic modeling and reusable business logic integrated into GitLab CI/CD workflows
Conducted architectural evaluations of Databricks, Snowflake, and AWS Athena to support future platform strategy decisions
Mentored a team of developers, optimizing development cycles and ensuring cloud data engineering best practices
Implemented IoT 4.0 pipelines for ingesting telemetry data and supporting predictive analytics initiatives

Sep 2021 - Sep 2022

1 year 1 month

Rottendorf, Germany

Kafka Expert

S.Oliver GmbH

Developed Spring Boot Kafka Streams applications
Created custom Kafka source connectors for SAP systems and custom sink connectors to write back to SAP
Deployed Kafka Connect connectors with monitoring on Azure Kubernetes Service
Developed data pipelines using Airflow and Azure Cloud
Architected data pipelines between on-premise and Azure Cloud
Wrote Spark jobs to clean and aggregate data

Feb 2021 - Aug 2022

1 year 7 months

Germany

Software Developer

RTL Deutschland

Designed and implemented a Lakehouse architecture combining Azure Databricks, Delta Lake, and Azure Synapse for batch and real-time workloads with ACID compliance
Built RESTful data APIs using FastAPI and deployed them via Azure App Services as a controlled access layer
Developed incremental ETL pipelines using PySpark and dbt, implementing star schema models for semantic consistency and historical tracking
Enabled interactive reporting and visual analytics using Power BI integrated into Azure
Implemented strong data access controls, audit logging, and resource monitoring for GDPR compliance and governance
Established automated CI/CD pipelines for data infrastructure using Azure-native tooling

Sep 2020 - Jun 2021

10 months

Munich, Germany

Cloud Solution Architect

Allianz Technology

Migrated data lakes into Azure Cloud with high automation using ArgoCD, Jenkins, Helm charts, and Terraform
Developed Spark jobs for data lake migration
Created Helm charts for Azure AKS automation
Refactored application designs to be cloud-native and onboarded internal customers to Azure
Implemented Spring Boot Kafka Streams applications and Argo workflow pipelines

Mar 2020 - May 2020

3 months

Munich, Germany

Big Data Architect, Data Architect

BMW AG

Developed data pipelines using Spark and Airflow for self-driving car data
Generated metrics for geospatial applications
Ingested data into Elasticsearch using Apache Spark
Applied functional programming principles with Scala

Jan 2020 - May 2020

5 months

Stuttgart, Germany

Big Data Developer

DXC

Automated Azure Kubernetes cluster deployments
Created and deployed deep learning Spark jobs with PyTorch and GPUs on Kubernetes
Performed GPU inferencing on terabytes of data

Sep 2017 - Jun 2018

10 months

Nuremberg, Germany

Big Data Developer, Spark / Kafka Developer, Data Architect

GfK

Wrote Kafka Connectors to ingest data into Accumulo in a Kerberized environment
Kerberized applications for Hadoop, Kafka, and Kafka Connect
Created statistic plans for RDF4J queries over Accumulo
Developed Apache NiFi workflows
Introduced Git flow, CI/CD, and Docker automation
Set up Kafka Connect with Kerberos on Google Kubernetes
Wrote Java applications based on RDF and web semantics

Apr 2017 - Sep 2017

6 months

Frankfurt, Germany

Big Data Architect

Deutsche Bahn

Sized and configured Hadoop clusters with Kerberos and Active Directory
Migrated data using Sqoop and managed workflows with Oozie
Implemented data pipelines using Kylo, Apache NiFi, and Talend
Deployed Hortonworks Cloud Break on AWS and Apache Storm streaming applications
Supported internal clients with streaming and data cleaning operations

Oct 2016 - Mar 2017

6 months

Dresden, Germany

Big Data Developer and Architect

Kiwigrid

Created Spark jobs for historical data reporting
Developed custom Spark data sources for HBase and aggregation for data exploration
Architected an alerting and computing framework based on Spark Streaming
Deployed applications using Docker

Industries Experience

See where this freelancer has spent most of their professional time. Longer bars indicate deeper hands-on experience, while shorter ones reflect targeted or project-based work.

Experienced in Transportation (3 years), Information Technology (2 years), Fashion (1.5 years), Retail (1.5 years), Media and Entertainment (1.5 years), and Insurance (1 year).

Transportation

Information Technology

Fashion

Retail

Media and Entertainment

Insurance

Business Areas Experience

The graph below provides a cumulative view of the freelancer's experience across multiple business areas, calculated from completed and active engagements. It highlights the areas where the freelancer has most frequently contributed to planning, execution, and delivery of business outcomes.

Experienced in Information Technology (7.5 years), Business Intelligence (5.5 years), and Product Development (0.5 years).

Information Technology

Business Intelligence

Product Development

Skills

General Skills:

Apache Spark
Java Mapreduce
Scala
Java
Python
Perl
Tornado
Rest Apis
Jira
Etl
Docker
Maven
Gradle
Kubernetes
Jenkins
Cloud Build
Azure Cosmos Db
S3
Neo4j
Azure Kubernetes Service
Aks
Flask
Spring Boot
Data Vault 2.0
Pytorch
Tensorflow
Azure Iot
Modbus
Mqtt
Opc
Plc
Azure Data Factory
Azure Synapse
Llm

Operating System Skills:

Aix
Ubuntu
Cento Os
Mac Osx
Windows Server 2008 R2
Flexframe
Routing
Git
Ibm Hadr
Ibm Tsm
Aws S3
Apache Mesos

Sap Skills:

Rfc
Snc
Charm
Kernel Upgrades
Ehp Upgrade
Ssfs
Sso
Hana

Databases:

Oracle 11
Db2
Sap Max Db
Mysql
Aws Redshift
Postgres

Cloud Technologies:

Aws Emr
Aws Glue
Aws Ecs
Aws S3
Google App Engine
Azure Kubernetes
Azure Containers

Languages

German

Advanced

English

Advanced

Certifications & licenses

Databricks Lakehouse Platform Accreditation

Confluent Certified Developer For Apache Kafka

Generative AI With Large Language Models (LLM)

CKAD: Certified Kubernetes Application Developer

Microsoft Certified: Azure Fundamentals

Data Engineering Nanodegree

Functional Programming Principles In Scala On Coursera

Big Data Analytics Fraunhofer IAIS

Big Data Analytics By University Of California, San Diego On Coursera

Databricks Developer Training For Apache Spark

Hadoop Platform And Application Framework By University Of California On Coursera

Machine Learning With Big Data By University Of California, San Diego On Coursera

SAP Os And Db Migration (Tadm70)

SAP Database Administration I (Oracle) (Adm 505)

SAP Database Administration II (Oracle) (Adm 506)

SAP Netweaver As Implementation Und Operation I (SAP Tadm10)

SAP Netweaver Portal - Implementation And Operation (Tep10)

ITL Foundation V4

Profile

Created

August 2025

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Frequently asked questions

Do you have questions? Here you can find further information.

Where is Jorge based?

Jorge is based in Würzburg, Germany.

What languages does Jorge speak?

Jorge speaks the following languages: German (Advanced), English (Advanced).

How many years of experience does Jorge have?

Jorge has at least 7 years of experience. During this time, Jorge has worked in at least 10 different roles and for 11 different companies. The average length of individual experience is 1 year and 7 months. Note that Jorge may not have shared all experience and actually has more experience.

What roles would Jorge be best suited for?

Based on recent experience, Jorge would be well-suited for roles such as: Data Architect, Data Architect Expert, Kafka Expert.

What is Jorge's latest experience?

Jorge's most recent position is Data Architect at Deutsche Bahn.

What companies has Jorge worked for in recent years?

In recent years, Jorge has worked for Deutsche Bahn, SAP AG, s.Oliver GmbH, ias Gruppe, and S.Oliver GmbH.

Which industries is Jorge most experienced in?

Jorge is most experienced in industries like Transportation and Logistics, Information Technology (IT), and Fashion and Apparel. Jorge also has some experience in Retail, Media, Entertainment and Publishing, and Insurance.

Which business areas is Jorge most experienced in?

Jorge is most experienced in business areas like Information Technology (IT), Business Intelligence, and Product Development.

Which industries has Jorge worked in recently?

Jorge has recently worked in industries like Transportation and Logistics, Information Technology (IT), and Fashion and Apparel.

Which business areas has Jorge worked in recently?

Jorge has recently worked in business areas like Information Technology (IT) and Business Intelligence.

Does Jorge have any certificates?

Jorge has 18 certificates. Among them, these include: Databricks Lakehouse Platform Accreditation, Confluent Certified Developer For Apache Kafka, and Generative AI With Large Language Models (LLM).

What is the availability of Jorge?

Jorge is immediately available for suitable projects.

What is the rate of Jorge?

Jorge's rate depends on the specific project requirements. Please use the Meet button on the profile to schedule a meeting and discuss the details.