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Deputy Manager, Analytics & Insights

Оценка ИИ

Отличная вакансия в топовой компании сферы кибербезопасности с фокусом на современные технологии (GenAI, Snowflake, dbt). Высокий уровень ответственности и возможность влиять на стратегию данных.


Вакансия из Quick Offer Global, списка международных компаний
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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Высокая сложность обусловлена необходимостью сочетать глубокие знания финансовой аналитики (SaaS метрики) с продвинутыми навыками дата-инженерии (Snowflake, dbt, Python) и внедрением GenAI.

Анализ зарплаты

Медиана45 000 $
Рынок35 000 $ – 60 000 $
Оценка ИИ

Зарплата для данной роли в Индии (Мохали) для уровня Deputy Manager в международной продуктовой компании обычно выше среднего по рынку, учитывая требования к GenAI и глубокому стеку данных.

Сопроводительное письмо

I am writing to express my strong interest in the Deputy Manager, Analytics & Insights position at Zscaler. With over 6 years of experience at the intersection of Finance and Data Engineering, I have developed a deep expertise in building scalable data architectures using Snowflake and dbt. My background in defining core SaaS metrics like ARR and NRR, combined with a rigorous approach to data modeling, aligns perfectly with your mission to professionalize the Finance data stack.

In my previous roles, I have successfully migrated legacy financial logic into modern, modular dbt environments and leveraged Python to automate complex workflows. I am particularly excited about Zscaler's focus on AI-forward initiatives; I have been experimenting with RAG and LangChain to automate business commentary and would welcome the opportunity to operationalize these GenAI use cases within your FP&A team. I am a pragmatic builder who values impact over activity and thrives in high-growth, high-accountability environments.

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Присоединяйтесь к лидеру в сфере кибербезопасности и внедряйте передовые GenAI решения в финансовую аналитику!

Описание вакансии

About Zscaler

Zscaler accelerates digital transformation to ensure our customers can be more agile, efficient, resilient, and secure. As an AI-forward enterprise, we are constantly pushing the envelope, leveraging the world’s largest security data lake to power our cloud-native Zero Trust Exchange platform. This innovation protects our customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location.

Here, impact in your role matters more than title and trust is built on results. We say, impact over activity. We seek innovators who actively use AI to amplify their impact and who thrive in an environment where we leverage intelligent systems to stay ahead of evolving threats. We believe in transparency and value constructive, honest debate—we’re focused on getting to the best ideas, faster. We build high-performing teams that can make an impact quickly and with high quality. To do this, we are building a culture of execution centered on customer obsession, collaboration, ownership, and accountability.

We value high-impact, high-accountability with a sense of urgency where you’re enabled to do your best work and embrace your potential. If you’re driven by purpose, thrive on solving complex challenges, and want to be part of the team that’s helping to secure the AI age, we invite you to bring your talents to Zscaler and help shape the future of cybersecurity.

Role

We are looking for a Deputy Manager - Analytics and Insights to join our FP&A Analytics team. This is a hybrid role based in our Mohali Office, reporting to the Manager - Analytics and Insights, FP&A.

As Deputy Manager, you will serve as the architect and technical strategist for Finance’s modern data ecosystem—defining the Source of Truth for core SaaS metrics and building scalable, trusted data products. You will lead the professionalization of the Finance data stack in Snowflake and dbt, enabling automated reporting, faster forecasting, and high-impact analytics. You will also prototype and operationalize GenAI use cases to reduce manual effort and improve decision-making.

What you’ll do (Role Expectations)

  • Define and own the governed, auditable data models for core SaaS metrics (ARR, NRR, and churn), ensuring all complex business logic is accurately translated into the data architecture
  • Utilize expert-level SQL and Python to design and build analytical datasets within Snowflake that power critical FP&A reporting, forecasting, and executive insights
  • Manage the Finance DBT environment by overseeing project structure, standards, testing strategies, and performance optimization, while migrating legacy logic into modern, modular facts and dimensions
  • Lead efforts to identify operational bottlenecks and develop robust SQL and Python frameworks designed to eliminate manual work and streamline financial data workflows
  • Spearhead the prototyping of RAG and LangChain-based solutions to provide automated business commentary and enhance self-serve insights through cutting-edge AI

Who You Are (Success Profile)

  • You act like an owner whose passion for the mission fuels a bias for action and an operation of high integrity. You adapt to what’s needed, navigating seamlessly between high-level strategy and hands-on execution.
  • You are a high-trust collaborator who is ambitious for the team, embracing a challenging culture by giving and receiving feedback with clarity and respect.
  • You are a pragmatic builder obsessed with creating, iterating, and shipping, balancing technical excellence with the need to deliver value quickly.
  • You are data-driven, using analytics to find the truth and value evidence over assumptions to drive better outcomes.
  • You think at scale, connecting your work to the global company mission and building solutions that are built to last in a high-growth environment.

What We’re Looking for (Minimum Qualifications)

  • 5–7+ years in Finance Analytics, Analytics Engineering, or Data Engineering with strong exposure to finance systems and metrics
  • Expert SQL with deep Snowflake experience including data modeling, optimization, and warehousing best practices at scale
  • Strong Python proficiency for data engineering and automation including APIs, pipelines, and frameworks
  • Significant hands-on DBT experience focusing on dependencies, testing strategy, standards, and CI/CD concepts
  • Practical experience designing and operating ELT pipelines and orchestration such as Airflow or Prefect along with dimensional and schema design

What Will Make You Stand Out (Preferred Qualifications)

  • Hands-on GenAI implementation experience with LangChain, LlamaIndex, or OpenAI APIs, ideally with RAG patterns applied to finance workflows
  • Proven mentorship or code review experience setting engineering standards and elevating junior analysts and engineers
  • Experience supporting SaaS at scale including hyper-growth metrics complexity, evolving governance, and multi-source finance data

#LI-HG1

#LI-Hybrid

At Zscaler, we are committed to building a team that reflects the communities we serve and the customers we work with. We foster an inclusive environment that values all backgrounds and perspectives, emphasizing collaboration and belonging. Join us in our mission to make doing business seamless and secure.

Our Benefits program is one of the most important ways we support our employees. Zscaler proudly offers comprehensive and inclusive benefits to meet the diverse needs of our employees and their families throughout their life stages, including:

  • Various health plans
  • Time off plans for vacation and sick time
  • Parental leave options
  • Retirement options
  • Education reimbursement
  • In-office perks, and more!

Learn more about Zscaler’s Future of Work strategy, hybrid working model, and benefits here.

By applying for this role, you adhere to applicable laws, regulations, and Zscaler policies, including those related to security and privacy standards and guidelines.

Zscaler is committed to providing equal employment opportunities to all individuals. We strive to create a workplace where employees are treated with respect and have the chance to succeed. All qualified applicants will be considered for employment without regard to race, color, religion, sex (including pregnancy or related medical conditions), age, national origin, sexual orientation, gender identity or expression, genetic information, disability status, protected veteran status, or any other characteristic protected by federal, state, or local laws. See more information by clicking on the Know Your Rights: Workplace Discrimination is Illegallink.

Pay Transparency

Zscaler complies with all applicable federal, state, and local pay transparency rules.

Zscaler is committed to providing reasonable support (called accommodations or adjustments) in our recruiting processes for candidates who are differently abled, have long term conditions, mental health conditions or sincerely held religious beliefs, or who are neurodivergent or require pregnancy-related support.

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Навыки

  • SQL
  • Python
  • Snowflake
  • dbt
  • Airflow
  • Prefect
  • Generative AI
  • LangChain
  • Data Modeling
  • SaaS Metrics
  • ETL

Возможные вопросы на собеседовании

Проверка понимания специфики SaaS-бизнеса и умения перекладывать бизнес-логику в код.

Как бы вы спроектировали модель данных в dbt для расчета Net Retention Rate (NRR), учитывая изменения в контрактах и валютные колебания?

Оценка технической экспертизы в основном стеке компании.

Опишите ваш опыт оптимизации производительности тяжелых запросов в Snowflake и подходы к организации CI/CD для dbt-проектов.

Проверка навыков автоматизации и владения Python.

Расскажите о самом сложном ETL-процессе или инструменте автоматизации, который вы разработали на Python для финансовых нужд.

Оценка готовности к инновациям, упомянутым в вакансии.

Как, по вашему мнению, архитектура RAG может улучшить процесс подготовки ежемесячных финансовых отчетов (business commentary)?

Проверка лидерских качеств и соответствия культуре 'ownership'.

Приведите пример, когда вы обнаружили критическую ошибку в данных или процессе: как вы ее устранили и какие системные изменения внедрили?

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