QlikView-разработчик (Python)

About the Team

Here at Avride, we're building the future with self-driving vehicles and delivery robots. As you can imagine, this creates a massive amount of data, and we need someone to help us connect the dots. This is a great opportunity to join a growing team and have a real, tangible impact on our technology and our success.

About the Role

We’re looking for a Data Analytics Engineer who is skilled in both data engineering and data analysis. Your main goal will be to take the messy, raw data coming from our vehicles, APIs, and databases, and transform it into clean, reliable datasets that everyone from our engineers to our CEO can actually use. You'll be responsible for building the data pipelines that make this happen, and the dashboards that bring the insights to life.

What You'll Do

• You'll tame our raw data streams, building the ETL pipelines that pull information from all corners of the company into our data warehouse.
• You'll work with some truly unique datasets—everything from vehicle sensor telemetry and logistics data to the results of our internal system tests.
• You'll write the smart, efficient SQL queries needed to shape our data and prepare it for analysis.
• You'll create and manage the Grafana dashboards that our teams rely on to track performance and spot issues.
• You'll work closely with other teams to figure out what data they need, and then you'll deliver it.
• You'll also get to experiment with our internal AI and LLM-based tools to find new ways to analyze data and automate insights.

What You'll Need

• Strong, practical experience with Python and its data libraries (like Pandas, Polars, etc.).
• Expert-level SQL. You should be very comfortable with complex joins, window functions, and query optimization.
• A solid background in building and maintaining ETL pipelines using modern tools.
• Hands-on experience with a BI tool like Grafana, Tableau, or Looker.
• Familiarity with workflow orchestrators like Airflow, Dagster, or Prefect.
• A good high-level understanding of how Large Language Models (LLMs) work and an interest in applying them to data problems.
• A strong sense of ownership and a passion for making sure the data is right.

Nice to Have

• You've worked with ClickHouse or other modern analytical databases (Snowflake, BigQuery, Redshift).
• You have experience with vehicle, sensor, or logistics data.
• You've worked in the autonomous vehicle or robotics industry before.

#LI-MS1

ИТ B2C — самая крупная экосистема в Сбере. Нас более 8000 человек в 18 городах России. Мы занимаемся разработкой и развитием розничных решений, помогая сделать сервисы Банка доступнее, безопаснее и удобнее.

• оперативная разработка и доработка витрин данных в BI-инструменте (АС Навигатор)

• написание и переписывание сложных SQL-запросов, оптимизация производительности запросов и работа с хранимыми процедурами

• разработка и доработка Python-скриптов в рамках пилотов с возможной интеграцией LLM (GigaChat)

• валидация чужого кода (SQL/Python), подготовка артефактов для передачи в смежные команды

• опыт работы с BI-инструментами (Tableau, Power BI, Superset и т.п.), включая оперативную отрисовку, доработку дашбордов, понимание пользовательских потребностей в данных. Умение проектировать логику витрин и визуализаций

• опыт разработки и доработка скриптов на Python (автоматизации, интеграции)

• уверенное владение SQL (PostgreSQL/Greenplum): сложные запросы, оптимизация, разработка витрин в BI-среде

• · практический опыт использования AI-ассистентов для кодинга (вайб-кодинг), написание промптов, работа с API моделей (GigaChat, GPT и др.)

• опыт работы с Git

• опыт ведения реестров, написания и поддержки документаций, работа в Jira/Confluence, контроль сроков

• формат работы - офис (БЦ Поклонка)

• ежегодный пересмотр зарплаты и годовая премия

• корпоративный спортзал и зоны отдыха

• более 400 образовательных программ СберУниверситета для профессионального и карьерного развития

• гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ

• расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа

• бесплатная подписка СберПрайм с возможностью совместного использования на трех близких, скидки на продукты компаний-партнеров

• вознаграждение за рекомендацию друзей в команду Сбера

• корпоративная пенсионная программа.

About TaxDome

At TaxDome, we're building the #1 practice management platform for accounting firms in the US and globally. Founded in 2017, we've grown into a 400+ fully remote team across 40+ countries, serving tens of thousands of businesses worldwide with millions of end clients.

How we work

You'll be part of a globally distributed team built on trust, ownership, and self-management.

We focus on outcomes over activity — prioritizing clear ownership, pragmatic decision-making, and accountability for results over rigid processes. Collaboration is central to how we operate: we communicate openly, involve the right people early, and continuously improve how we build products and teams together.

About this role

We're hiring a Staff Analytics Engineer to join TaxDome's data team — the group building and owning the analytics warehouse on BigQuery. You'll work across the full data lifecycle: designing and evolving data models, onboarding new sources, building analytics for product and business teams, and contributing to AI-native workflows and agentic pipelines. The team works AI-first — Claude Code and LLM tooling are embedded in the daily workflow, not an experiment.

It’s a fully remote role, we are hiring across European timezones.

Our tech stack

• Cloud: Google Cloud Platform (BigQuery, GCS, GKE/Kubernetes)
• DWH: BigQuery (cross-region, column-level security, PII masking)
• Transformations & data load: dbt & Python
• Orchestration: Apache Airflow on Kubernetes, Python ETL
• BI: Data Studio
• Process: GitLab, CI checks for layer architecture, AI-assisted code review
• AI: Claude Code, LLM-driven development and analytics

What you'll be responsible for

• Onboard new data sources end to end — from raw ingestion to certified marts.
• Advance data quality: tests, contracts, metrics dashboards, and anomaly monitoring.
• Contribute to warehouse architecture evolution: conventions, code review, documentation, and AI-ready data contracts.
• Build and maintain dashboards for product and business teams; design metrics and bring them to self-service.
• Drive analytical work from business question to reproducible analysis with a clear decision recommendation.
• Develop models and analyses with AI assistants (Claude Code and similar) as a primary workflow, not a shortcut.
• Help build AI-native team processes: automating routine work, agentic pipelines for documentation, testing, and ad-hoc analysis.
• Act as the translator between business questions and data model design.

What you bring

Must-have

• Proven depth in data roles — analytics engineering, data analysis with an engineering orientation, or data engineering with strong analytical capability.
• Advanced SQL — you write and review complex queries comfortably and reason about performance trade-offs.
• Hands-on production experience with dbt: incremental models, snapshots, tests, macros, and project organisation.
• Experience designing DWH layers and reasoning about trade-offs: normalisation vs. marts, full rebuild vs. incremental, SCD2.
• Python for ETL tasks and data analysis.
• Experience building dashboards and metrics with the ability to drive analysis through to a decision — not just a table.
• Real, embedded experience working with AI assistants in your daily workflow — LLMs as a core tool, not an occasional experiment.
• Experience with Airflow or another orchestration platform
• Advanced stakeholder and project management: able to take a vague business problem, decompose it into a plan, and drive it to completion independently.

Nice-to-have

• SaaS product analytics background: PLG metrics, funnel analysis, cohort modelling.
• Experience with GA4, HubSpot, or Stripe data.
• Understanding of data privacy requirements: GDPR, PII masking, policy tags.
• Experience building agentic pipelines or automations on top of LLM APIs.

What we offer

At TaxDome, we aim to create an environment where people can do their best work and grow alongside the company.

• Competitive compensation, paid in USD, transparently shared before the first interview
• Performance-based incentive plan
• Fully remote work with flexible hours
• 30 paid days off annually, plus sick days as needed
• Health & well-being support
• Learning & development budget to support your professional growth
• English lessons reimbursement
• Co-working space reimbursement
• Company-provided equipment (conditions may vary depending on the role)
• A high level of autonomy and ownership in your work
• The opportunity to make a real impact in a fast-growing global SaaS company
• A collaborative, international team with a strong product mindset

Upon successful completion of the interview process and acceptance of the offer to join, an employment verification check will be conducted as part of pre-boarding — confirming job titles and dates of engagement with 2 of your previous employers. This is a required step for all new joiners.

If you're excited about this opportunity and believe you could make an impact at TaxDome, we'd love to hear from you!
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