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Senior Analytics Engineer – Cloud & FinOps
JFrog — лидер рынка с отличной репутацией. Вакансия предлагает работу с передовым стеком (AI-assisted tools) и решение сложных задач на стыке Data и Cloud Platform Engineering, что гарантирует профессиональный рост.
Сложность вакансии
Роль требует редкого сочетания навыков: глубокой экспертизы в Data Engineering (SQL, Python, ETL) и понимания специфики облачной инфраструктуры (FinOps, Kubernetes, биллинг). Высокая сложность обусловлена необходимостью работать с огромными объемами данных в мультиоблачной среде.
Анализ зарплаты
Зарплата в вакансии не указана, но для позиции Senior Analytics Engineer в Бангалоре в международной продуктовой компании уровня JFrog, рыночные ожидания обычно находятся в верхнем дециле. Предлагаемый диапазон соответствует стандартам для опытных специалистов в технологических хабах Индии.
Сопроводительное письмо
I am writing to express my strong interest in the Senior Analytics Engineer – Cloud & FinOps position at JFrog. With a robust background in SQL, Python, and data modeling, I have spent years building scalable data pipelines that bridge the gap between infrastructure telemetry and business value. My experience in multi-cloud environments aligns perfectly with JFrog's large-scale operations across AWS, Azure, and GCP.
In my previous roles, I have focused on developing analytical frameworks for cloud cost allocation and unit economics, which directly supports your FinOps initiatives. I am particularly excited about JFrog's emphasis on leveraging AI-driven analytics tools like Claude and Cursor to enhance pattern detection and decision support. I am confident that my technical expertise in Snowflake/BigQuery and my ability to translate complex infrastructure data into actionable insights will help your engineering teams optimize cloud spend and operational efficiency.
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Откликнитесь в jfrog уже сейчас
Присоединяйтесь к JFrog в Бангалоре, чтобы внедрять инновации в FinOps и управлять облачной аналитикой в глобальном масштабе!
Описание вакансии
Fast-Frogward Your Career to Years From Now
JFrog is the only end-to-end software supply chain platform that provides complete visibility, security, and control for automating the delivery of trusted releases from code to production. Our platform enables organizations to manage, secure, and automate their software delivery process, fueling innovation without worry. We empower companies to build and release software faster and more securely than ever before.
With over 7,500 customers worldwide, including many Fortune 100 companies, JFrog is at the forefront of global innovation. Join us in shaping the future of software delivery and contributing to solutions that empower some of the world's most influential industries.
We are seeking a Senior Analytics Engineer – Cloud & FinOps to help drive data-driven decision making across our cloud infrastructure and platform operations.
This role will focus on building analytics solutions that provide visibility into cloud costs, infrastructure utilization, and platform usage patterns. The engineer will develop data pipelines, analytical models, and automated insights that connect cloud billing data, infrastructure telemetry, and business metrics. Working closely with Cloud Platform Engineering, SRE, and Product teams, this role will help the organization better understand how infrastructure usage and engineering decisions impact cloud spend and operational efficiency.
Our platform operates in a large-scale multi-cloud environment, generating significant volumes of infrastructure and operational data. The ideal candidate enjoys working with complex datasets and building analytical systems that help engineering teams understand cost drivers, infrastructure behavior, and system efficiency.
In addition, the role is expected to leverage modern AI-driven analytics tools and models (e.g., LLM-based analysis, automated insight generation, and intelligent data exploration) to enhance data processing, pattern detection, and decision support capabilities. Experience working with such tools is highly valued.
What will be your core responsibilities
- Analyze cloud cost and usage data across multiple cloud providers to identify cost drivers, trends, and optimization opportunities.
- Develop analytical frameworks that connect infrastructure usage, operational metrics, and business activity.
- Support FinOps initiatives by improving visibility into how platform workloads and engineering decisions influence cloud spend.
- Investigate cloud cost anomalies and infrastructure changes to identify root causes and improvement opportunities.
- Design and maintain data pipelines and transformations that ingest data from sources such as:
- cloud billing exports
- infrastructure telemetry
- operational metrics
- internal product and business systems
- Build scalable analytics datasets and data models optimized for infrastructure and cost analysis.
- Ensure data accuracy, consistency, and governance across analytical datasets
- Analyze large datasets to identify relationships between system behavior, infrastructure utilization, and cloud cost patterns.
- Develop analytical frameworks supporting:
- cloud cost allocation and unit economics
- infrastructure utilization analysis
- capacity planning
- operational performance monitoring
- Translate complex datasets into clear insights and recommendations for engineering and leadership teams.
- Leverage modern AI-assisted tools to accelerate data exploration, analysis, and investigation.
- Build automated workflows that help teams identify cost anomalies, usage trends, and system behavior changes more efficiently.
Required Skills for this role
- Strong SQL and data modeling expertise
- Python for data analysis and automation
- Experience building data pipelines and ETL/ELT workflows
- Strong analytical thinking and problem-solving skills
- Experience working with large-scale operational or infrastructure dataset
- Experience using AI-assisted development tools such as Cursor, Claude, Copilot, or similar
- Experience working with modern data platforms such as: Redshift, BigQuery, Snowflake
- Experience with analytics and visualization tools such as: Tableau / Looker / Power BI / QuickSight
- Experience working with cloud infrastructure data (AWS, Azure, or GCP)
- Familiarity with cloud billing datasets and cost management analytics
- Experience analyzing large-scale infrastructure or telemetry data
- Experience working in FinOps, cloud operations, platform engineering, or infrastructure analytics environments
- Familiarity with Kubernetes or distributed systems environments
- Strong analytical and problem-solving abilities
- Ability to translate complex infrastructure data into clear and actionable insights
- Comfortable working in cross-functional engineering environment
NOTE: We are located in Bangalore (Bellandur) and follow a 3 days from office (mandatory), hybrid work model.
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Навыки
- SQL
- Python
- Data Modeling
- ETL
- ELT
- Redshift
- BigQuery
- Snowflake
- Tableau
- Looker
- Power BI
- QuickSight
- AWS
- Azure
- GCP
- Kubernetes
- FinOps
- Cursor
- Claude
- GitHub Copilot
Возможные вопросы на собеседовании
Проверка понимания специфики FinOps и умения работать с сырыми данными облачных провайдеров.
Как бы вы спроектировали пайплайн для объединения данных о биллинге из AWS CUR и Azure Usage Details для расчета Unit Economics конкретного продукта?
Оценка навыков оптимизации и работы с большими данными.
Опишите ваш подход к выявлению аномалий в расходах на облачную инфраструктуру. Какие статистические методы или AI-инструменты вы бы использовали?
Проверка владения современным стеком, указанным в вакансии.
Каков ваш опыт использования AI-ассистентов (например, Cursor или Claude) для ускорения разработки аналитических моделей или отладки сложных SQL-запросов?
Оценка понимания инфраструктурного контекста.
Как изменения в конфигурации Kubernetes (например, лимиты ресурсов) влияют на ваши аналитические модели стоимости и утилизации?
Проверка навыков коммуникации с бизнесом.
Как вы объясните техническому руководству разницу между 'waste' (расточительством) и необходимым масштабированием инфраструктуры, используя только данные?
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