freiberufler Senior Data Engineer auf freelance.de

Senior Data Engineer

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  • 01.01.2026

Kurzvorstellung

Senior Date Engineer mit mehr jähirger Erfahrungen in den Bereichen Big Data Integration, Data Warehouse, Cloud Computing und Advanced Analytics.

Qualifikationen

  • Amazon Web Services (AWS)5 J.
  • Apache Spark5 J.
  • Big Data3 J.
  • Data Vault Modeling
  • Data Warehousing3 J.
  • Databricks2 J.
  • Datenmodelierung4 J.
  • ETL5 J.
  • Generative KI2 J.
  • Java (allg.)
  • MLOps2 J.
  • Projektmanagement (IT)4 J.
  • Python/Pandas, Pyspark, Polars
  • Requirement Analyse4 J.

Projekt‐ & Berufserfahrung

Senior Data Engineer (Festanstellung)
Kundenname anonymisiert, Düsseldorf
1/2024 – offen (2 Jahre, 9 Monate)
Chemieindustrie
Tätigkeitszeitraum

1/2024 – offen

Tätigkeitsbeschreibung

Eingesetzte Qualifikationen

Big Data, Data Warehousing, Databricks, Generative KI, MLOps

Data Engineer (Festanstellung)
Kundenname anonymisiert, Düsseldorf
7/2019 – 12/2023 (4 Jahre, 6 Monate)
Versicherungen
Tätigkeitszeitraum

7/2019 – 12/2023

Tätigkeitsbeschreibung

- As the lead data engineer, successfully led the engineering of data processing pipelines in multiple high-profile projects, utilizing cutting-edge technologies like Apache Spark to efficiently process structured and semi-structured data. These pipelines improved processing times, scalability, and data quality for the organization.
- Collaborated with Data Scientists to develop data-driven solutions that achieved seven-digit cost savings and revenue increase for the organization. Through close collaboration and a deep understanding of the business requirements, we identified critical areas for improvement and designed innovative solutions that delivered substantial value. Additionally, established MLOps approach with AWS Sagemaker for streamlined development and deployment of machine learning models.
- Successfully led a project on implementing dynamic pricing for automotive insurance, which enabled the business to access near-real-time data for pricing optimizations. Managed the end-to-end project lifecycle, including requirements gathering, project planning, team coordination, and stakeholder management. Delivered the project within the allocated budget and timeline, resulting in increased revenue and improved customer satisfaction.

Eingesetzte Qualifikationen

Amazon Web Services (AWS), Apache Spark, Datenmodelierung, ETL, Projektmanagement (IT), Python, Requirement Analyse

Big Data DevOps Streaming
Kundenname anonymisiert, Nürnberg
4/2019 – 6/2019 (3 Monate)
Banken
Tätigkeitszeitraum

4/2019 – 6/2019

Tätigkeitsbeschreibung

• Successfully migrated complex vert.x based microservices to Self-Containing Services using Spring Boot, Spring Cloud, and
Apache Camel. Overcame numerous challenges during the migration process, resulting in a more maintainable system.
• Led the effort to perform comprehensive performance testing of existing infrastructure using jMeter and implemented
integration tests to ensure system reliability and scalability. As a result of these efforts, we were able to identify and resolve
critical performance bottlenecks, resulting in a more efficient and robust system.

Eingesetzte Qualifikationen

Java (allg.), Spring Framework, Apache Camel

Data Engineer (Festanstellung)
Kundenname anonymisiert, Köln
4/2018 – 4/2019 (1 Jahr, 1 Monat)
Versicherungen
Tätigkeitszeitraum

4/2018 – 4/2019

Tätigkeitsbeschreibung

Building a scalable big data pipeline moving streaming data and batched data to a data lake on AWS Cloud:
• Data integration from variety of data sources (e.g. relational data from IBM Mainframe, Oracle, MS SQL Server, SAP BW and web services data from check24, German weather portal) with Informatica Data Integration Tool and AWS Glue
• Writing python code for automatic generation of Informatica mappings, sessions and workflows
• Deployment of Streaming Platform Confluent Kafka, which is one of the main building blocks for data ingestion process
• Deployment of AWS S3 storage for persistent storages of unstructured and semi-structured data within the data lake
• Deployment of a cloud-based data warehouse AWS Snowflake for persistent storages of structured and semi-structured data within the data lake

Eingesetzte Qualifikationen

ETL, Amazon Web Services (AWS), Apache Spark, Big Data, Cloud Computing, Data Warehousing, Python

Ausbildung

Informatik - Data and Software Engineering
M.Sc.
2017
Technische Universtität Berlin

Weitere Kenntnisse

Data Platform:
- Databricks
- AWS SageMaker/EMR/Athena
- Google BigQuery
- PostgreSQL
- DB2
- Oracle

ETL / ELT Tool:
- Python (Jupyter Notebook)
- AWS EMR, Glue
- DBT
- Apache Kafka
- Informatica Data Integration

Data Warehouse Modeling:
- Dimension Modeling
- Data Vault Modeling

Cloud technology:
- Amazon Web Services
- Google Cloud

Programming skills:
- Python
- SQL
- Scala
- Java

Advanced Analytic / Machine Learning:
- Spark MLlib
- Scikit-learn
- Keras

Persönliche Daten

Sprache
  • Deutsch (Muttersprache)
  • Englisch (Fließend)
Reisebereitschaft
auf Anfrage
Arbeitserlaubnis
  • Europäische Union
Home-Office
bevorzugt
Profilaufrufe
483
Berufserfahrung
10 Jahre und 3 Monate (seit 06/2016)
Projektleitung
3 Jahre

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