Data Analyst

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SeniorZdalnie·WarszawaInne·B2B

#464724·Dodano dziś·0

Źródło: justjoin.it

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Tech Stack / Keywords

Python RDBTSQL Databricks

Podsumowanie oferty

The Data Analyst will identify business trends and opportunities with Product, Growth, Finance, and Operations leadership. The role combines SQL data modeling with dashboards and narrative reports to support decision-making, alongside data quality and workflow automation.

Wymagania

2–5 years of experience in a data analytics, product analytics, or business intelligence role.
Strong mastery of SQL, including window functions, CTEs, and performance optimization, and familiarity with modern data transformation practices.
Hands-on experience with cloud data warehouses such as Snowflake, BigQuery, or Databricks, and with BI or semantic-layer tools.
Ability to translate quantitative findings into actionable recommendations for non-technical stakeholders.
Understanding of statistical concepts including hypothesis testing, confidence intervals, and regression analysis.
Basic knowledge of Git/GitHub workflows for managing analytics code.

Nice to have:

Experience using dbt for analytics engineering.
Proficiency in Python or R for exploratory data analysis, automation, or statistical modeling.
Experience with product analytics platforms such as Mixpanel, Amplitude, or PostHog.
Background in agile or Scrum environments.

Obowiązki

Insight Generation & Business Strategy:

Partner with cross-functional leadership across Product, Growth, Finance, and Operations to identify trends, diagnose churn and growth drivers, and discover business opportunities.

Analytics Engineering & Data Modeling:

Write clean, modular, version-controlled SQL models, using tools such as dbt, to transform raw data into structured, production-ready tables.

Modern Visualization & Storytelling:

Design dashboards and narrative reports using Lightdash, Looker, Metabase, Tableau, or Power BI to drive decision-making.

Data Quality & Governance:

Establish data definitions, document metrics in a central data catalog, and ensure data accuracy, testing, and reliability.

AI & Workflow Automation:

Use AI-assisted analytics workflows and automated pipelines to speed up data exploration and deliver real-time operational alerts.

RED Global

30 aktywnych ofert

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