Docker
Kubernetes
Python
Machine Learning (ML)
Data AnalyticsRole & responsibilities:
- Developing ETL pipelines for data replication
- Analyze, query and manipulate data according to defined business rules and procedures
- Manage very large-scale data from a multitude of sources into appropriate sets for research and development for data science and analysts across the company
- Convert prototypes into production data engineering solutions through rigorous software engineering practices and modern deployment pipelines
- Resolve internal and external data exceptions in timely and accurate manner
- Improve multi-environment data flow quality, security, and performance
Skills & qualifications:
- Must have experience with:
- virtualization, containers, and orchestration (Docker, Kubernetes)
- creating log ingestion pipelines (Apache Beam) both batch and streaming processing (Pub/Sub, Kafka)
- workflow orchestration tools (Argo, Airflow)
- supporting machine learning models in production
- Have a desire to continually keep up with advancements in data engineering practices
- Strong Python programming and exploratory data analysis skills
- Ability to work independently and with team members from different backgrounds
- At least a bachelor's degree in an analytical or technical field. This could be applied mathematics, statistics, computer science, operations research, economics, etc. Higher education is welcome and encouraged.
- 3+ years of work in software/data engineering.
- Superior interpersonal, independent judgment, complex problem-solving skills
- Global orientation, experience working across countries, regions and time zones
Shubham Vishwakarma
Full Stack Developer - Averlon
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Full Stack Developer - Averlon