Data Engineer - Azure (4-6 yrs)

Salary : 6 - 17LPA

Data Engineer(Azure)

Job Brief :

The successful applicant will be working within a highly specialised and growing team to enable delivery of data and advanced analytics system capability.

Roles and Responsibility :

- Develop and implement a reusable architecture of data pipelines to make data available for various purposes including Machine Learning (ML), Analytics and Reporting

- Work collaboratively as part of team engaging with system architects, data scientists and business in a healthcare context

- Define hardware, tools and software to enable the reusable framework for data sharing and ML model productionization

- Work comfortably with structured and unstructured data in a variety of different programming languages such as SQL, R, python, Java etc

- Understanding of distributing programming and advising data scientists on how to optimally structure program code for maximum efficiency

- Build data solutions that leverage controls to ensure privacy, security, compliance and data quality

- Understand meta-data management systems and orchestration architecture in the designing of ML/AI pipelines.

- Deep understanding of cutting edge cloud technology and frameworks to enable Data Science

- System integration skills between Business Intelligence and source transactional

- Improving overall production landscape as required

- Define strategies with Data Scientists to monitor models post production

- Write unit tests and participate in code reviews

Skill Requirement :

- Expert in programming languages such as R, Python, Scala and Java

- Expert database knowledge in SQL and experience with MS Azure tools such as Data Factory, Synapse Analytics, Data Lake, Databricks, Azure stream analytics and PowerBI

- Modern Azure datawarehouse skills Consulting Services (Tech Talents | Contracting & Permanent) | Solution Engineering | SaaS Products (Consulting, Implementation & User-adoption)

- Expert Unix/Linux admin experience including shell script development

- Exposure to AI or model development

- Experience working on large and complex datasets

- Understanding and application of Big Data and distributed computing principles (Hadoop and MapReduce)

- ML model optimization skills in a production environment

- Production environment machine learning and AI

- DevOps/DataOps and CI/CD experience

Technical skills additional : AWS experience

Qualification : Bachelor's or Master's degree in Computer Science or related field.