Jobs at CloudThat

Supports and optimizes AWS cloud infrastructure and data platform services, including EC2, EKS, EFS, MSK, EMR, and Glue. Responsibilities include provisioning, monitoring, troubleshooting, incident management, root-cause analysis, container and Kubernetes administration, storage and backup support, big data and streaming operations, CloudWatch monitoring, and production on-call support in a 24x7 environment.

Provides first-level technical and operational support to enterprise clients through calls, email, chat, and service portals. Manages incidents, service requests, escalations, ticket queues, SLA compliance, documentation, reporting, and customer communications. Troubleshoots software, hardware, application, access, and basic networking issues; supports root-cause analysis, knowledge management, process improvement, and mentoring of junior team members in a rotational 24x7 environment.

Design cloud-native data and AI architectures, including data lakes, warehouses, ETL/ELT pipelines, real-time streaming systems, and infrastructure as code. Review architectural patterns, optimize performance and costs, align delivery with business objectives, support client presentations and workshops, and mentor junior team members. The role requires cloud solution design experience across AWS or Azure, knowledge of data and AI patterns, AI algorithm evaluation, communication skills, and an AWS Certified Solutions Architect Professional certification.

Designs cloud-native data and AI architectures, including data lakes, warehouses, ETL/ELT pipelines, real-time streaming, and infrastructure as code. The role evaluates cloud storage and processing options, optimizes performance and costs, guides architectural development, supports client workshops, aligns technical delivery with business objectives, and mentors junior team members. AWS or Azure expertise, AI algorithm experience, and AWS Certified Solutions Architect Professional certification are required.

Build and maintain ETL pipelines for a large-scale analytics platform, ensure data quality, resolve data issues, handle support tickets, and assist senior engineers with enhancements. The role requires SQL and Python skills, basic cloud data platform knowledge, and familiarity with AWS Glue, Lambda, Redshift, and Apache Airflow. Experience in the Oil & Gas domain is preferred.

Design and implement cloud-native data lakes, warehouses, AI architectures, ETL/ELT pipelines, and real-time data systems. Guide architectural patterns, optimize performance and costs, align technical delivery with business goals, support client workshops, and mentor junior team members. The role requires expertise across major cloud platforms, data engineering tools, infrastructure as code, AI algorithm evaluation, and cloud solution architecture.

Develop and maintain scalable Python data pipelines, ETL processes, workflow automation, and dataset integrations. Ensure data quality, validation, performance, and production reliability while supporting analytics and machine learning teams. Work with databases, cloud data services, APIs, orchestration tools, and deployment platforms to deliver clean, production-ready data solutions.

Leads cloud proofs of concept, architecture validation and implementation across multi-cloud environments. Troubleshoots cloud platforms, resolves complex technical issues, applies networking, system administration, security, monitoring and automation best practices, and mentors junior associates. Requires deep AWS expertise, experience managing multi-cloud and multi-account environments, certification in at least two cloud platforms, and team leadership experience.

Develop and convert B2B sales pipelines, achieve annual targets, prospect and qualify leads, negotiate and close deals, collaborate with OEMs and distributors, and maintain weekly and monthly sales reports. The role requires independently generating opportunities, explaining technology solutions, managing stakeholder relationships, and selling to potentially large organizations with multiple decision-makers.

Designs secure, scalable, and cost-optimized cloud architectures across AWS, Azure, and GCP for enterprise clients. Leads discovery sessions, creates solution blueprints, architecture diagrams, Statements of Work, proposals, and pricing estimates. Conducts technical workshops, feasibility and risk assessments, proposal walkthroughs, and executive briefings while guiding internal delivery teams. Requires cloud architecture, migration, security, automation, GenAI, and strong client-facing communication skills.

Design, develop, maintain, and optimize scalable ETL pipelines and data workflows for a large-scale analytics platform. Ensure data reliability, manage production pipelines, resolve tickets within SLA, support P1/P2 incident resolution, and collaborate with data and application development teams. The role is based onsite in Mumbai and requires client site visits.

Lead proof-of-concepts, cloud architecture validation and implementation across multi-cloud environments. Troubleshoot cloud platforms, resolve complex technical problems, enforce cloud, networking, security, and monitoring best practices, and mentor junior associates. The role requires deep AWS expertise, multi-account experience, cloud automation knowledge, certification in at least two cloud platforms, and team leadership experience.

Develop and maintain scalable Python-based data pipelines, ETL processes, workflow automations, and dataset integrations. Ensure data quality, validation, performance, and integrity while deploying and monitoring production workflows. Collaborate with data engineers, analysts, stakeholders, and machine learning teams to provide reliable, production-ready data solutions. Work with databases, cloud data services, orchestration tools, APIs, and CI/CD practices.

Design scalable and secure cloud architectures aligned with RTO/RPO and stakeholder needs. Lead solutioning workshops and demonstrations, create architecture documentation, and guide cloud migration and transformation initiatives. Advise teams on architecture implementation, CI/CD pipelines, DevOps, Kubernetes, containers, cost optimization, disaster recovery, data analytics, and machine learning. Mentor teams while ensuring enterprise-level architecture standards and client-focused outcomes.

Designs and maintains enterprise backend microservices for a large-scale analytics platform using Java, Spring Boot, and AWS. Responsibilities include building and optimizing REST APIs, deploying containerized services, handling production support tickets, and promoting code quality and modern application architecture.