09.02.2025 aktualisiert
Premiumkunde
100 % verfügbarSenior Software and Data Engineer
Düsseldorf, Deutschland
Weltweit
Master of ScienceSkills
Programming Languages: Python, Java, SQL
Cloud Services:
DevOps – CI/CD Tools: Docker, Terraform, Jenkins, GitLab, Git, GitHub Actions
RDBMS: MySQL, MariaDB, Microsoft SQL Server, PostgreSQL, Oracle
Platforms / Frameworks / Libraries: Apache Airflow, Kafka, dbt, Jupyter, Zeppelin, JSF, JMS, REST APIS, Swagger, Hibernate, ORM, Apache Spark, PySpark, Pandas, Numpy, Scrum, Kanban, Jira.
Cloud Services:
- Amazon Web Services: AWS EC2, S3, RDS
- Azure: VMs, Blob Storage
- Google Cloud: Bigquery, Cloud Functions, PubSub, Cloud Run, Cloud Composer
- Snowflake: Data warehousing, ETL/ELT Pipelines, task graphs, streams, integration, data sharing
DevOps – CI/CD Tools: Docker, Terraform, Jenkins, GitLab, Git, GitHub Actions
RDBMS: MySQL, MariaDB, Microsoft SQL Server, PostgreSQL, Oracle
Platforms / Frameworks / Libraries: Apache Airflow, Kafka, dbt, Jupyter, Zeppelin, JSF, JMS, REST APIS, Swagger, Hibernate, ORM, Apache Spark, PySpark, Pandas, Numpy, Scrum, Kanban, Jira.
Sprachen
DeutschgutEnglischMutterspracheFranzösischMutterspracheItalienischMuttersprache
Projekthistorie
- Designed and implemented ETL / ELT pipelines in CloudComposer (Airflow) to load data from REST APIs, Kafka topics, on-prem databases, files and other sources. Integrated the data into the company’s GCP BigQuery data warehouse. Implemented advanced data conversion functionality in Java, Python and SQL. Prepared CI/CD pipelines in GitLab using Terraform.
- Migrated old pipelines to dbt.
- Designed and implemented ETL / ELT pipelines to load data from a wide range of available sources using GCP’s Pub/Sub, Cloud Functions, Dataflow (Java), Google Cloud Storage, Bigquery, and Apache Airflow. Sources included MySQL, Oracle, Adobe Analytics, Google Analytics and PostGreSQL.
- Implemented data transformation layer bringing clean, reliable data for data scientists using Python (Numpy, Pandas), SQL, dbt, GCloud CLI scripts, Cloud Composer (Airflow), and Apache Spark (PySpark).
- Implemented deployment solutions within the CI/CD process to allow fast and cost-effective training of ML models using Docker containers, Jenkins, Gitlab, Git.
- Automated data distribution to internal stakeholder using JMS, Pub/Sub, Cloud Functions and Airflow on Linux VMs.
- Developed and implemented companywide KPI visualization concept using Geckoboard, Tableau, and Superset.
- Built RESTful APIs on Google Cloud Run using Docker containers and FastAPI
- Designed and built Operational Risk Management software currently licensed and used at client financial institutions in Switzerland. Tech stack: Java, JMS, JSF, MySQL, Apache Tomcat, Linux, Hibernate, ORM. The application was deployed both on AWS, using EC2, S3 and RDS, and on Microsoft Azure using Azure VMs and Blob storage.
- Implemented reporting and visualizations on PowerBI
- Created eLearning modules increasing operational risk awareness in banks.
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