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# Data Analyst

- **Company:** Trinsik GmbH
- **Location:** Wien, Austria (Remote available)
- **Experience:** Experienced
- **Salary:** €60,000.0 - €65,000.0
- **Contract:** Permanent contract
- **Skills:** Query Performance, Data Analysis, Microsoft Azure, Databases, Extract Transform Load (ETL), Data Warehousing, Relational Databases, Dimensional Modeling, Google Analytics, Power BI, Mixpanel, Standard Sql, SQL Databases, Usage Analysis, Snowflake, Powerquery, Amplitude Analytics
- **Published:** October 30, 2026
- **Apply:** https://www.xing.com/jobs/vienna-data-analyst-158821027

## About the Role

* 3-5 years of experience as a Data Analyst, Product Analyst, Analytics Engineer, or similar role.
 * Business-fluent German and excellent English.
 * Strong SQL - joins, CTEs, window functions, and enough understanding of query performance to know why something is slow.
 * Strong experience with Power BI (data modeling, DAX, Power Query, report creation) or comparable BI tools.
 * Solid understanding of data modeling (star schema / dimensional modeling), relational databases, and ETL/ELT processes.
 * Hands-on experience with product analytics and event tracking (GA4, Amplitude, Mixpanel, PostHog or similar), including the metrics that go with it - activation, retention, cohorts, funnels.
 * Comfortable with commercial metrics: unit economics, CAC/LTV, contribution margin, pricing logic.
 * You organise yourself: you can take an unclear requirement, structure it, and drive it without someone breaking it down for you.
 * Comfortable presenting your own results to client stakeholders.
 * Analytical mindset with a structured and solution-oriented approach.
 * Proven stakeholder management and project ownership experience in client-facing settings.
 * Experience in requirements gathering and translating business needs into concrete technical requirements and data tasks for engineers and analysts.
 * Completed IT-related education or equivalent qualification., * Familiarity with investment or financial data (portfolio analytics, performance metrics, fund reporting).
 * Experience with Microsoft Azure, Fabric, dbt, Snowflake, or a similar modern data stack.
 * Python for data work.

## Description

We are looking for a Data Analyst with 3-5 years of experience to join our data team in Vienna. You will own the analytics layer in our client and venture projects, across three kinds of work: product analytics for the digital products we build, commercial analytics for new services and business models, and investment and portfolio analytics for our (Corporate) Venture Capital and Investment clients. You will work alongside our data engineers and get hands-on with the pipelines and models behind your dashboards.

 * Set up and run product analytics for our digital products and ventures: define the event and tracking concept, build funnel, retention, and cohort analyses, and answer why users do what they do.
 * Build the commercial analytics for new services - unit economics, pricing scenarios, contribution margin, adoption and revenue development - and make the numbers defensible for management-level decisions.
 * Work with our (Corporate) Venture Capital and Investment clients on the data models and reporting behind portfolio monitoring, performance tracking, and investment decision-making.
 * Write and optimise SQL for data models, transformations, and analyses - you are comfortable in the database, not just in the BI tool.
 * Support our data engineers on pipelines and the transformation layer: build models, add tests, fix data quality issues, extend existing flows.
 * Build and maintain dashboards and reports (primarily Power BI) that people actually use - for portfolio monitoring, product KPIs, and commercial performance.
 * Manage stakeholders on the client side - from business owners to management: align expectations, define business metrics and KPIs with them, and make sure analytics stays tied to their strategic goals.
 * Lead client requirements gathering and translate business questions into clearly scoped, prioritised data tasks for the data team (engineering and analytics), including acceptance criteria and data sources.
 * Continuously improve data quality, documentation, and governance across projects.
 * Take project ownership for your data workstream: break down the work, set priorities, keep scope, timelines and dependencies visible, and coordinate with engineers, PMs, and the client.
 * Take a topic from the first requirements workshop to a running, documented solution, and share what you learn within the analytics community at Trinsik.