Вакансии

* Take ownership of customer onboarding and ensure successful adoption of the solution. * Monitor device health, system performance, and customer usage data to identify risks and opportunities.

Location: Bengaluru, Karnataka, India, APAC From Fivetran’s founding until now, our mission has remained the same: to make access to data as simple and reliable as electricity. With Fivetran, customer data arrives in their warehouses, canonical and ready to query, with no engineering or maintenance required. We’re proud that more organizations continue to leverage our technology every day to become truly data-driven. About Us Fivetran and dbt Labs are bringing together two industry-leading companies with a shared mission: helping organizations unlock the full value of their data. Together, we’re delivering the data infrastructure layer that helps organizations move, transform, and trust their data — from the moment data moves, through every transformation, to the context teams and AI systems rely on. Fivetran helps organizations automate data movement across the systems, clouds, engines, and tools they rely on. dbt Labs pioneered analytics engineering, helping teams transform data into reliable, governed insights. Together, we support thousands of organizations as they build a trusted foundation for analytics, AI, and better business decisions. As we bring our teams and technology together, we’re building on the strengths of both companies while continuing to deliver the products and experiences our customers know and trust. It’s an exciting time to join us: we’re creating a company with the scale, talent, and technology to help more organizations put their data to work with greater speed, confidence, and impact. During this transition period, you may see references to both Fivetran and dbt Labs throughout our recruiting process as we integrate our teams, systems, and career sites. About the Role We're looking for a Senior Financial Systems Analyst who will drive the transition from manual, repetitive legacy work to more accurate, streamlined, and automated models, dashboards, and data feeds. Your work will change from week-to-week and month-to-month as you partner with FP&A to redesign how the team plans and forecasts, build new dashboards, and train AI agents to do the tedious stuff automatically. We need someone who combines financial acumen with technical know-how — translating model assumptions and drivers into the right long-term solution, whether that's a Pigment model, a Python script, or an AI agent. You'll also own the trustworthiness of the numbers Finance leaders rely on, building systematic data-quality checks and partnering with the Data/Analytics Engineering team to resolve upstream data issues. And because a fix that only you can maintain isn't really a fix, you'll document your models clearly enough that analysts without a Pigment or Python background can self-serve basic changes — empowering the team with tools that completely solve problems without manual workarounds. This is a full-time position based out of our Bangalore office. Our hybrid work model offers a blend of remote flexibility and in-person collaboration, including two days in the office each week to connect and build as a team. Technologies You’ll Use Pigment, BigQuery, NetSuite, Omni, Sigma, Claude Code What You’ll Do Partner directly with FP&A business partners across Sales & Marketing, R&D, and G&A to understand how each team plans, forecasts, and reports today, then work together to identify manual, repetitive Finance work that Pigment integrations, Python scripts, and AI agents can streamline and automate. Own the end-to-end build of new and migrated Pigment models — data blocks, formulas, workflows, dashboards, and views — turning fuzzy business asks from FP&A into technical solutions people actually want to use. Collaborate on the design and maintenance of our Pigment architecture, ensuring we avoid a tangled mess of metrics, dimensions, and boards and keep our tools easy-to-navigate. Team up with your peers on the Finance Systems team to build durable integrations between Pigment, BigQuery, and other finance systems, so the data everyone needs shows up accurately and automatically instead of through manual workarounds. Put systematic data-quality checks in place — reconciliations, change monitoring, variance alerts — so business partners can trust the numbers without manual effort. Document what you build clearly enough that a Finance analyst with no Pigment or Python background can self-serve basic changes. Loop in the Data/Analytics Engineering team when a request needs a new data connection or you find an upstream data problem. Skills We’re Looking For 5+ years of experience in financial systems, FP&A, or analytics engineering, with hands-on work in an EPM platform (Pigment, Anaplan, Adaptive, or similar) — or an equivalent analytics-engineering background (SQL, dbt, Python) with a strong interest in moving into EPM/finance systems work. Proven experience using AI agents/LLM tooling to automate finance workflows. Ability to sit with a Finance stakeholder, listen to a messy description of “how we currently do this,” and come back with a well-scoped technical plan. Working proficiency in Python — or willingness and ability to learn via Claude Code or Codex. Strong SQL skills and comfort working in a cloud data warehouse (BigQuery or similar). High attention to detail — this role will work on models that inform real business decisions, so the ability to audit models and build intuition on outputs matter as much as speed. Strong communication skills — able to explain a data discrepancy or a modeling trade-off to someone without a systems or data background. Bonus Skills​ Prior experience inside an FP&A or corporate finance function (not just building tools for one from the outside), ideally supporting a Sales, R&D, or G&A finance function specifically. Prior experience building a Sales Capacity/Planning model or a Supply Chain model in Pigment, Anaplan, or another similar planning platform. Familiarity with BI tools such as Tableau, Looker, Sigma, or Omni. Experience with dbt or another data-transformation framework. # LI-HYBRID #LI-DB1 Perks and Benefits 100% employer-paid medical insurance * Generous paid time away from work, including paid vacation or flexible/unlimited vacation depending on role and country, plus paid sick time, inclusive parental leave, paid holidays, including a year-end Global Week of Rest, and volunteer days off. RSU stock grants* Professional development and training opportunities Company virtual happy hours, free food, and fun team-building activities Monthly cell phone stipend Access to an innovative mental health support platform that offers personalized care and resources in areas such as: therapy, coaching, and self-guided mindfulness exercises for all covered employees and their covered dependents. * May vary by country and worker type - please reach out to your recruiter for more information Click here to learn more about Fivetran's Benefits by Region. We’re honored to be valued at over $5.6 billion , but more importantly, we’re proud of our core values of Get Stuck In, Do the Right Thing, and One Team, One Dream . Read about us in Forbes . Fivetran brings together high-quality talent across the globe to make data access as easy and reliable as electricity for our customers. We value and recognize that our customers benefit from having innovative teams made of people from many backgrounds, experiences, and identities. Fivetran promotes diversity, equity, inclusion & belonging through attracting, recruiting, developing, and retaining a diverse workforce, not only because it is the right thing to do, but because it helps us build a world-class company to better serve our customers, our people and our communities. To learn more about Fivetran’s culture and what it’s like to be part of the team, click here and enjoy our video. To learn more about our candidate privacy policy, you can read our statement here . We are committed to ensuring that all candidates have an equal opportunity to participate in our interview process. If you require accommodations at any stage of the process due to a disability, medical condition, or any other circumstance, please don't hesitate to submit your request by filling out this form . We will work with you to provide reasonable accommodations to facilitate your participation and ensure a fair and accessible interview experience. Your request and any information provided will be kept confidential and will not impact your candidacy. We look forward to hearing from you and accommodating your needs to the best of our ability.

– Исследовать и прототипировать новые методы контроля качества данных на наших данных. – Проектировать ML- и статистические контроли для выявления аномалий, дрейфа распределений, деградации свежести данных, нарушений сезонных паттернов и нетипичных комбинаций метрик.

• Разработка моделей для recommendation, ranking, forecasting, pricing и optimization. • Тестирование гипотез и проведение экспериментов.

• Разработка AI-продуктов и agentic workflows. • Интеграция LLM и создание RAG-систем.

▪️Разработка uplift-моделей для оценки инкрементального эффекта коммуникаций и офферов на поведение клиентов. ▪️Построение моделей склонности и ценности оффера для клиента.

• Build and maintain data pipelines and integrations with source systems (ERP K-Soft / 1С, Qlik Sense); • Strong Python (pandas, scikit-learn, and ML/DL frameworks) and SQL;

💎Опыт работы с AWS, Terraform, Ansible, L2/L3 concepts, CI/CD tools, Docker, Kubernetes, Python, Bash.

🔎 Maqsad: Egallangan bilimlarni esdan chiqarmaslik. 📚 Texnologiya: Php, Dart, Kotlin, Java, Python.

— Разработка backend и frontend веб-приложений и внутренних систем. — Python (Litestar/FastAPI), async API.

• 7+ лет опыта с SQL. • 5+ лет опыта с Python, Power BI, DAX.

Обязательные требования: — Опыт участия во внедрении систем планирования спроса или автоматизации процессов прогнозирования. — Понимание процесса demand planning: исторические продажи, очистка данных, статистический прогноз, экспертные корректировки, сценарии и оценка точности. — Опыт разработки или настройки решений на low-code платформе: от модели данных и логики расчётов до пользовательских экранов и тестирования. — Уверенное понимание реляционной модели данных и SQL: соединения таблиц, фильтрация, агрегация, проверка и преобразование данных. — Понимание того, как Python-компоненты получают данные из платформы, обрабатывают их и возвращают результат; способность разбирать конфигурацию и диагностировать ошибки на стыке компонентов. — Навыки взаимодействия с заказчиком и разработки понятной документации. Дополнительные требования: — Опыт работы с In.Plan Demand Planning или другой платформой IBP/S&OP. — Практический опыт работы с Python, датафреймами и параметрической настройкой алгоритмов. — Знакомство с моделью данных «звезда» по Кимбаллу, Airflow и BI-инструментами, например Superset. Задачи на проекте: — Собирать и уточнять требования планировщиков спроса, продаж и смежных команд; описывать целевой процесс, сценарии работы и функциональные требования. — Проектировать и настраивать модель данных: таблицы, наборы данных, справочники, иерархии, связи, показатели и уровни планирования; готовить настройки чтения, записи и преобразования данных. — Разрабатывать решение средствами low-code платформы: ракурсы планирования, экраны, предупреждения, права доступа и пользовательские сценарии. — Настраивать параметры очистки истории, сегментации и алгоритмов прогнозирования спроса с использованием библиотеки модулей In.Plan Demand; проверять качество исходных данных и результатов расчёта. — Прорабатывать сценарии ручной корректировки, обогащения и согласования прогноза, включая формирование итогового плана спроса. — Разбирать и проверять SQL-запросы и преобразования данных, понимать передачу данных между платформой и Python-алгоритмами; формулировать задачи на доработку там, где платформенных средств недостаточно. — Готовить инструкции и обучающие материалы, проводить обучение пользователей и сопровождать запуск решения в эксплуатацию. Этапы отбора: 1. Внутренний квалификационный. 2. Интервью с клиентом с техническими вопросами. Описание проекта и команды: Специалист разрабатывает решение для планирования спроса на low-code платформе In.Plan по бизнес-требованиям заказчика. Проектирует и настраивает модель данных, логику обработки и интерфейсы, связывает платформенные настройки с алгоритмами на Python и проверяет результат вместе с пользователями.

• 5+ лет продакшен-опыта в бэкенде на любом современном языке (Java, Go, Rust, Python, Ruby) и готовность перейти на .NET. • 2+ года разработки микросервисов.

Требуется Devops. • от 3х лет на позиции Senior.

• Развивать и сопровождать CI/CD-пайплайны проверки безопасности ПО (security gate). • Встраивать новые инструменты анализа, автоматизировать проверки.

Мы ищем Head of DWH - лидера, который сочетает глубокую техническую экспертизу в DWH/ClickHouse, архитектурное мышление и управленческие навыки.

We're now looking for an experienced Marketing Data Analyst to strengthen our analytics team and help turn data into insights that drive smarter decisions, improve channel performance, and optimize marketing investments. About the team Our analytics team helps the business make smarter, data-driven decisions.

✓ 3+ years in market/quant risk. ✓ Derivatives & risk modeling.