Přeskočit na obsah Přeskočit na zápatí

Senior Data Engineer

Podrobnosti o osobě
510789
Zveřejněno od
26-Čer-2026
Obor
Research & Development
Společnost
Siemens Healthcare Private Limited
Úroveň zkušeností
S dlouholetou praxí v oboru
Název pozice
Plný úvazek
Režim práce
Pouze na pracovišti
Druh smlouvy
Trvalý
Lokalita
  • Bengalúru - Karnátaka - Indie
Role Overview
We are looking for a Data Engineer to support and enhance the CS-AT platform, which processes large-scale machine log data (15–20 years) to enable predictive and proactive maintenance solutions. The role involves building and optimizing data pipelines, log processing systems, and analytics platforms on Azure.
Key Responsibilities
Design, build, and maintain scalable data pipelines
Handle ingestion and processing of large-scale log data
Monitor and optimize pipeline performance and reliability
Work on log parsing and pattern extraction
Collaborate with data scientists on predictive and proactive maintenance use cases
Develop and optimize queries using KQL (Kusto Query Language)
Build and support dashboards using Azure Data Explorer
Ensure data quality, monitoring, and operational stability
Support integration with downstream systems such as OneAI and MI Log Interpreter
Required Skills
Core Skills
Strong experience in data engineering (5–6 years)
Expertise in writing KQL 
Expertise in building data pipelines and ETL/ELT processes
Experience with log data processing and analysis
Python and C# language skills
Azure Technologies
Azure Functions
Azure Event Grid
Azure Data Explorer (Kusto)+KQL
Azure Data Factory
Databricks/Spark
Delta Lake
Data & Engineering Skills
Pipeline monitoring and optimization
Performance tuning of large data systems
Handling high-volume historical datasets
Experience in distributed data processing
Documentation according to CS standards
Good to Have
Experience with predictive maintenance use cases
Exposure to machine logs / IoT / telemetry data
Understanding of data science workflows
Soft Skills
Strong problem-solving ability
Data Product Ownership mindset (Development + Operations)
Ability to work in cross-functional teams
Proactive approach to optimization and operations
Team Structure
Part of a (4 – 6) member cross-functional team including Development and Operations.
Key Success Metrics
Stable and optimized data pipelines
Improved processing efficiency
Reliable log ingestion and analysis
Smooth integration with AI systems