We are looking for an experienced Data Engineer with a passion for RF technology to join our leading tech team. The role includes:
Designing, developing, and optimizing Big Data infrastructures for Real-Time processing.
Building and managing Data Pipelines in Python (including Threads, asyncio, multiprocessing).
Managing ETL/ELT processes with Kafka, PostgreSQL, Redis, Amazon S3, and Kubernetes.
Supporting Machine Learning workflows, including Data Prep and Feature Store.
Developing APIs using FastAPI/Flask.
Working with cloud infrastructures and Kubernetes, optimizing resources.
Handling RF data: ingestion, basic signal processing, and parsing various formats.
Integrating with data storage systems.
Maintaining thorough documentation using Jira and Confluence.
Job location- Central
Scope of hours: 100 hours.
Designing, developing, and optimizing Big Data infrastructures for Real-Time processing.
Building and managing Data Pipelines in Python (including Threads, asyncio, multiprocessing).
Managing ETL/ELT processes with Kafka, PostgreSQL, Redis, Amazon S3, and Kubernetes.
Supporting Machine Learning workflows, including Data Prep and Feature Store.
Developing APIs using FastAPI/Flask.
Working with cloud infrastructures and Kubernetes, optimizing resources.
Handling RF data: ingestion, basic signal processing, and parsing various formats.
Integrating with data storage systems.
Maintaining thorough documentation using Jira and Confluence.
Job location- Central
Scope of hours: 100 hours.
Requirements:
Student in Electrical/Electronic Engineering, Software Engineering, or Computer Science.
3+ years of Data Engineering experience with Big Data and Real-Time Processing.
Proficiency in Python (Threads, asyncio, multiprocessing).
Experience building Data Pipelines in Python.
Hands-on experience with Kafka, PostgreSQL, Redis, Amazon S3.
ETL/ELT experience with structured and unstructured data.
Experience with Airflow, Luigi, or Prefect.
Kubernetes and CI/CD pipeline management.
Linux environment experience.
Strong self-learning and teamwork skills.
RF technology familiarity – significant advantage.
Docker experience.
Big Data/Streaming systems experience.
Knowledge of HDF5, Protocol Buffers, TCP, SMB.
Machine Learning process support experience .
Student in Electrical/Electronic Engineering, Software Engineering, or Computer Science.
3+ years of Data Engineering experience with Big Data and Real-Time Processing.
Proficiency in Python (Threads, asyncio, multiprocessing).
Experience building Data Pipelines in Python.
Hands-on experience with Kafka, PostgreSQL, Redis, Amazon S3.
ETL/ELT experience with structured and unstructured data.
Experience with Airflow, Luigi, or Prefect.
Kubernetes and CI/CD pipeline management.
Linux environment experience.
Strong self-learning and teamwork skills.
RF technology familiarity – significant advantage.
Docker experience.
Big Data/Streaming systems experience.
Knowledge of HDF5, Protocol Buffers, TCP, SMB.
Machine Learning process support experience .
This position is open to all candidates.
