2 Data storage Jobs in Chennai | Data storage Job openings in Chennai

Exp - 8+ Yrs

Backup Storage

Location - Banglore/Chennai

5 days WFO

Description: Storage, Backup and Cyber Resiliency SME

Location-Bangalore,chennai

Role Title: Storage, Backup and Cyber Resiliency SME / Lead Engineer

Role Summary: We are looking for a strong Storage, Backup and Cyber Resiliency SME with hands-on experience across on-premises, colocation, VMware, AWS, VMC on AWS, NetApp, Dell storage and enterprise backup environments. The candidate should be able to assess the current storage and backup landscape, reduce dependency on vendors, identify operational gaps, support cloud migration initiatives, and improve service transparency, resiliency, utilization, and cost optimization across hybrid infrastructure environments.

Key Responsibilities

• Assess and document the current storage, backup, cyber recovery, VMware, cloud and colocation footprint across APAC, EMEA and North America environments.
• Work closely with vendor teams, cloud teams, VMware teams, application teams and internal stakeholders to clarify ownership, map dependencies and resolve operational gaps.
• Manage storage administration activities including provisioning, capacity planning, utilization monitoring, performance review, allocation, expansion and day-to-day support.
• Support backup administration, restore operations, retention policy alignment, backup failure resolution and long-term retention requirements including seven- and ten-year compliance-driven retention.
• Support migration from legacy colo and VMware environments to AWS, VMC on AWS, EC2, FSx for ONTAP and future GCP environments where applicable.
• Implement and support cyber resiliency capabilities including immutable backups, cyber vaulting, clean-room recovery, isolated recovery environments, data scanning and RTO/RPO validation.
• Drive cost optimization by analyzing storage allocation, snapshot retention, backup utilization, infrastructure sizing and lower-cost platform alternatives.
• Contribute to automation using Terraform or similar infrastructure automation tools for repeatable provisioning, configuration and operational efficiency.

We are looking for an outstanding ML Architect (Deployments) with expertise in deploying Machine Learning solutions/models into production and scaling them to serve millions of customers. A candidate with an adaptable and productive working style which fits in a fast-moving environment.

Skills:

- 5+ years deploying Machine Learning pipelines in large enterprise production systems.

- Experience developing end to end ML solutions from business hypothesis to deployment / understanding the entirety of the ML development life cycle.
- Expert in modern software development practices; solid experience using source control management (CI/CD).
- Proficient in designing relevant architecture / microservices to fulfil application integration, model monitoring, training / re-training, model management, model deployment, model experimentation/development, alert mechanisms.
- Experience with public cloud platforms (Azure, AWS, GCP).
- Serverless services like lambda, azure functions, and/or cloud functions.
- Orchestration services like data factory, data pipeline, and/or data flow.
- Data science workbench/managed services like azure machine learning, sagemaker, and/or AI platform.
- Data warehouse services like snowflake, redshift, bigquery, azure sql dw, AWS Redshift.
- Distributed computing services like Pyspark, EMR, Databricks.
- Data storage services like cloud storage, S3, blob, S3 Glacier.
- Data visualization tools like Power BI, Tableau, Quicksight, and/or Qlik.
- Proven experience serving up predictive algorithms and analytics through batch and real-time APIs.
- Solid working experience with software engineers, data scientists, product owners, business analysts, project managers, and business stakeholders to design the holistic solution.
- Strong technical acumen around automated testing.
- Extensive background in statistical analysis and modeling (distributions, hypothesis testing, probability theory, etc.)
- Strong hands-on experience with statistical packages and ML libraries (e.g., Python scikit learn, Spark MLlib, etc.)
- Experience in effective data exploration and visualization (e.g., Excel, Power BI, Tableau, Qlik, etc.)
- Experience in developing and debugging in one or more of the languages Java, Python.
- Ability to work in cross functional teams.
- Apply Machine Learning techniques in production including, but not limited to, neuralnets, regression, decision trees, random forests, ensembles, SVM, Bayesian models, K-Means, etc.

Roles and Responsibilities:

Deploying ML models into production, and scaling them to serve millions of customers.

Technical solutioning skills with deep understanding of technical API integrations, AI / Data Science, BigData and public cloud architectures / deployments in a SaaS environment.

Strong stakeholder relationship management skills - able to influence and manage the expectations of senior executives.
Strong networking skills with the ability to build and maintain strong relationships with both business, operations and technology teams internally and externally.

Provide software design and programming support to projects.

 Qualifications & Experience:

Engineering and post graduate candidates, preferably in Computer Science, from premier institutions with proven work experience as a Machine Learning Architect (Deployments) or a similar role for 5-7 years.