Azure Devops Data Engineer

• Azure cloud
  –Devops, CICD, Artifactory and experience in migrating application to cloud
• Data Science
  – Experience in Model ops, understanding of AIML model monitoring metrics and model development
• Data engineering
  – Airflow, ELK, Dockers and Kubernetes
• Strong hands on in Python and SQL
• · Data Science and data engineering
  
  Experience with good understanding of
  Data Science, Azure Dev Ops , Azure data factory, Model Ops, Python, SQL, Dashboarding, Model Ops, Airflow, CI/CD, Kubernetes, Kibana and model governance
• · Demonstrates a strong capacity to understand client needs and collaborate effectively with both internal teams and external stakeholders to achieve successful project outcomes. This involves actively listening to client feedback, translating business requirements into actionable technical tasks, and fostering open communication channels throughout the project lifecycle. By engaging in regular status updates and collaborative planning sessions, ensures alignment of project objectives, timely delivery of milestones, and overall client satisfaction.
• · Ability to quickly learn and adapt to emerging tools and technologies, as well as support the team in understanding and ramping up on new platforms or frameworks through effective knowledge sharing and training sessions.
• · Data Engineering Ability to manage, preprocess, and pipeline large datasets efficiently.
• · Machine Learning:
  Strong understanding of ML algorithms, model monitoring, and evaluation techniques.
• · Understanding of AI, ML and GenAI application post production monitoring metrics
• · Performance monitoring of AI/ML Models, understanding of metrics for model monitoring and maintenance.
• · Dev Ops:
  Strong experience with CI/CD pipelines, containerization (e.g., Docker), orchestration (e.g., Kubernetes), and automation tools.
• · Cloud Computing:
  Experience with cloud platforms such as Azure, Cloud for scalable deployment and management.
• · Experience in onboarding applications in Azure cloud
• · Software Development:
  Proficiency in Python programming languages; version control (e.g., Git).
• · Hands on with SQL and experience in Postgres
  
  SQL DB
• · Monitoring & Maintenance:
  Skills in deploying monitoring solutions, troubleshooting, and maintaining model performance in production.
• · Utilise Airflow for data orchestration, develop DAGs, and effectively troubleshoot any issues
• · Security & Compliance:
  Knowledge of data privacy, security best practices, and regulatory requirements.
• · Collaboration & Communication:
  Ability to work with cross-functional teams and clearly document processes and findings.

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