Data Analyst

Red Global Zobacz wszystkie oferty

Warszawa

6 dni temu

W skrócie

Red Global seeks a Data Analyst in Warsaw. Responsibilities include data modeling, dashboard creation, and insight generation. Requires 2-5 years of experience, advanced SQL, and BI tools. Skills in Git/GitHub and statistics are needed.

Słowa kluczowe

sql dbt bi tools data warehousing git github data modeling data analysis business intelligence statistics

Skrót przygotowany przez AI na podstawie treści ogłoszenia.

Key Responsibilities

Insight Generation & Business Strategy: Partner with cross-functional leadership (Product, Growth, Finance, Operations) to identify trends, diagnose churn/growth drivers, and discover high-value business opportunities.
Analytics Engineering & Data Modeling: Write clean, modular, and version-controlled SQL models (using tools like dbt) to transform raw data into well-structured, production-ready tables.
Modern Visualization & Storytelling: Design intuitive, dynamic dashboards and narrative reports (using Lightdash, Looker, Metabase, Tableau, or Power BI) that drive decision-making rather than just display metrics.
Data Quality & Governance: Establish data definitions, document metrics in a central data catalog, and ensure high standards for data accuracy, testing, and reliability.
AI & Workflow Automation: Leverage AI-assisted analytics workflows and automated pipelines to speed up data exploration and deliver real-time operational alerts.

Requirements & Qualifications

Experience: 2–5 years of experience in a data analytics, product analytics, or business intelligence role.
Advanced SQL & Modeling: Strong mastery of SQL (window functions, CTEs, performance optimization) and familiarity with modern data transformation practices.
Modern Data Stack: Hands-on experience with cloud data warehouses (e.g., Snowflake, BigQuery, Databricks) and BI/semantic layer tools.
Business Acumen & Storytelling: Ability to translate complex quantitative findings into clear, actionable recommendations for non-technical stakeholders.
Analytical & Statistical Mindset: Solid understanding of basic statistical concepts (hypothesis testing, confidence intervals, regression analysis).
Version Control & Collaboration: Basic knowledge of Git/GitHub workflow for managing analytics code.

Nice-to-Haves

Experience using dbt (data build tool) for analytics engineering.
Proficiency in Python or R for exploratory data analysis, automation, or statistical modeling.
Experience with product analytics platforms (e.g., Mixpanel, Amplitude, PostHog).
Background in agile/scrum environments.