We’re seeking an innovator with a strong track record as a Python or Data Engineer to drive forward the software design, implementation, and maintenance of our Remote Monitoring Patient Platform (RPMP) for processing, analysis and storage of digital biomarker data.
responsibilities :
Maintain and develop large scale data pipelines, enhance existing capabilities and enable their seamless integration & deployment into scalable Azure cloud environments
Innovate to increase efficiency of technical components
Participate in Scrum ceremonies to achieve sprint goals
Gain expert knowledge in key software components & services
Conduct code reviews and guide deep technical discussions
Collaborate with colleagues across multiple product teams (e.g. DevOps, Data Engineers, Data Scientists, Cloud Engineers, Solution Architects, and Python Engineers)
requirements-expected :
Multi-year experience with Python in a professional environment
Experience with large scale cloud based solutions (e.g. Microsoft Azure)
Expertise in and experience with Git, Docker, CI/CD solutions (e.g. Gitlab, Azure DevOps), Kubernetes, MongoDB
Ability to work in a team, manage competing priorities, and communicate effectively with both technical and non-technical stakeholders
Expertise in agile software development methodologies (e.g. SCRUM) and DevOps based development lifecycles preferred
2+ years of working with programming language focused on data pipelines,eg. Python or R
1+ years of experience working on GCP, Cloud (AWS/Azure/Google) or other cloud platform (optional)
1+ years of experience in data pipelines maintenance
1+ years of experience with different types of storage (filesystem, relation, MPP, NoSQL) and working with various kinds of data (structured, unstructured, metrics, logs, etc.)
1+ years of experience in working in data architecture concepts (in any of following areas data modeling, metadata mng., workflow management, ETL/ELT, real-time streaming, data quality, distributed systems)
2+ years of experience working with SQL
Exposure to open source and proprietary cloud data pipeline tools such as Airflow, Glue and Dataflow (optional)
Very good knowledge of relational databases (optional)
Very good knowledge of Git, Gitflow and DevOps tools (e.g. Docker, Bamboo, Jenkins, Terraform
