Research Scientist, Kaggle
Google (10000+ pracowników)
Programowanie Frontend
Programowanie Backend
Poland
Pełny etat
Law
Doctoral degree
Java
Master's degree
C++
JavaScript
Natural language processing
AI
Python
Mobile devices
Data Engineers - Remote Poland or Romania
Strategicsiq
Testy automatyczne IT
Administracja systemami
Data Science
Inżynieria danych
Inżynieria chmurowa
Just Join IT
Poland
Bucharest(Romania)
Zdalnie
Pełny etat
Mid
5,250 - 6,300 EUR / miesiąc
Big Data
Data modeling
ETL
Java
GCP
SOAP
REST API
Kafka
Role Overview
We are seeking a highly skilled Senior Data Engineer / ML Engineer with strong expertise in building scalable ELT/ETL pipelines, cloud-native data architectures, and API-driven integrations. The ideal candidate will have hands-on experience in Google Cloud Platform (GCP), Data Vault modeling, and the ability to translate complex business logic into robust engineering pipelines and data models.
Key Responsibilities
Design, develop, and maintain scalable ELT/ETL data pipelines on GCP.
Build and optimize data engineering pipelines for structured, semi-structured, and streaming data.
Implement and manage ML engineering workflows for production deployment.
Develop and maintain REST/SOAP APIs for system integrations.
Architect and implement Data Vault models for enterprise data warehousing.
Design event-driven architectures using Pub/Sub and streaming frameworks.
Integrate third-party systems into enterprise data ecosystems.
Collaborate with business stakeholders to translate business requirements into scalable data models and pipelines.
Ensure adherence to security best practices (IAM, VPC Service Controls, encryption, service accounts).
Optimize SQL queries and data performance in BigQuery.
Support reporting and analytics solutions (Power BI preferred).
Required Skills & Expertise
Strong experience building scalable ELT/ETL pipelines, ML engineering workflows, and API integrations (REST/SOAP).
Hands-on expertise within the GCP ecosystem: Dataform, Cloud Run, Pub/Sub, BigQuery (advanced SQL), GCS, and Firestore.
Solid understanding of Data Vault modeling and enterprise data architecture principles.
Experience designing event-driven and streaming architectures (Kafka, Pub/Sub).
Working knowledge of GKE, Spark, and Java-based data processing solutions.
Familiarity with MCP integration and TMF protocols.
Strong ability to translate business requirements into scalable data models and engineering pipelines.
Experience implementing cloud security best practices including IAM, VPC Service Controls, service accounts, and encryption.
Exposure to Power BI for reporting and analytics is an added advantage.