Live opening · Posted 4 days ago

Associate Data and Cloud Engineer

WhyMinds Global · Mumbai, Maharashtra, India (On-site)
Linkedin No
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At a glance

The key details from the original listing.

Posted 4 days ago
CompanyWhyMinds Global
LocationMumbai, Maharashtra, India (On-site)
Work modeNo
SourceLinkedin
Listed4 days ago

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About the role

Description supplied by the original job listing.

Company Description WhyMinds Global is a deep tech startup focused on building AI-driven technology products and consulting solutions for sectors such as Banking and Financial Services, E-commerce, Digital Media, Regulatory Compliance, and Cybersecurity. We designs intelligence-led platforms and tools that are regulated, robust, and ready for scale. Team members work on cutting-edge AI and cloud technologies that power secure, high-performance digital experiences. Joining WhyMinds Global offers exposure to complex real-world problems and opportunities to contribute to scalable, future-ready solutions.
Role Description The Associate Data & Cloud Engineer is a full-time, on-site role based in Mumbai. This role involves supporting the design, deployment, and maintenance of cloud infrastructure, ensuring systems are secure, reliable, and scalable. The engineer collaborates with software development teams to streamline releases, troubleshoot system issues, and improve overall performance and observability. The position also includes documenting configurations, following best practices for security and compliance, and participating in continuous improvement of DevOps workflows along with managing entire Data & Cloud Engineering.
-Monitor data quality of objects stored on S3 buckets. Emit the custom AWS Cloudwatch metrics and set up alarms for anomalies.
- Implement a semantic data modeling layer that centralizes metrics used within the organization.
- Fine-tune dbt models processing real-time data.
- Propose a KPI measuring the impact of a given recommendation engine.
- Implement a reverse-ETL pipeline using Airbyte.
- Create a data model of advertisements impression using real-time, high-volume events in SQL language (dbt models).
- Optimize Redshift queries.
- Build and maintain highly-responsive data dashboards and visualizations (either in Metabase or a chosen framework).
- Nurture data quality by implementing atomic data-oriented tests.
What you'll do:
Cloud Infrastructure Management:
Design, manage, and optimize cloud infrastructure using AWS and Azure.
Implement and maintain high-availability, scalable, and cost-effective cloud architectures.
Automation & CI/CD:
Automate continuous integration and delivery using Git or Bitbucket.
Create, maintain, and improve build pipelines using GitLab and Jenkins.
Automate infrastructure provisioning and configuration using Terraform, Ansible, or other IaC tools.
Microservices & Containerization:
Design, deploy, and manage microservices, databases, and front-end applications using container orchestration platforms like Kubernetes.
Work on end-to-end deployment pipelines, containerized applications, and environments.
Testing & Code Quality:
Integrate automated testing and code quality checks within pipelines using tools for unit testing, integration testing, and static code analysis.
Monitoring & Observability:
Set up and maintain observability systems, including monitoring, logging, and alerting for APIs, databases, network, and user interfaces.
Use tools like Prometheus, Grafana, ELK, and CloudWatch to ensure high system reliability and performance.
Open Source Adoption & Cost Optimization:
Research and implement open-source frameworks for authentication, authorization, workflows, health monitoring, business rules, document management, and service management to minimize cloud managed service costs.
Apply FinOps strategies to monitor and reduce cloud operational expenses while ensuring performance and scalability.
Preferred Qualification:
Hands-on experience in open-source tools
Good experience in Data Engineering, building data pipelines, end to end Devops lifecycle
Candidate must be able to join within 10 Days / Immediate Joining preferred
Demonstrated experience operating production Azure environments
Experience supporting AI/LLM workloads (local or API-based) in production
Comfortable working in a small startup team where you own outcomes, not just task
Experience assessing and improving inherited infrastructure (not just building greenfield)

Work arrangement
No

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