Job
In this role, you will develop data models, define metrics, close instrumentation gaps, and collaborate closely with product managers to create accurate analyses and dashboards for informed decision-making.
Job technologies
Your role in the team
- Understand the business. Learn which decisions Product, Customer Success, Operations and leadership need to make, and turn that into prioritized use cases, metric definitions and source requirements.
- Build the foundations. Bring the analytics perspective to stack, ingestion and warehouse design. Own the conventions for transformation, naming, testing and documentation.
- Model product usage and operations. Build clean models for activation, adoption, retention and customer health, as well as for support, implementation projects and delivery efficiency.
- Make metrics and data trustworthy. Define and document core metrics, resolve conflicting definitions, and put tests, freshness checks and clear ownership on every important model.
- Close instrumentation gaps. Work with engineers to design events and source data that make future analysis reliable.
- Measure what we ship. Partner with Product Managers on A/B tests, staged rollouts and feature-flag experiments, from hypotheses and guardrail metrics to an honest reading of the results.
- Enable self-service. Build marts, a semantic layer, dashboards and documentation, and run hands-on sessions that help colleagues use data well.
Our expectations of you
Qualifications
- Advanced SQL and solid Python, including query optimization in a cloud warehouse (e.g. Snowflake, BigQuery, Databricks, ClickHouse).
- Hands-on dbt or similar. Airflow or Dagster is a plus.
- Solid grasp of dimensional modeling, event data, SCDs and metric design.
- Engineering habits: Git, code review, testing, CI/CD, documentation.
- Strong product sense and the ability to turn vague questions from non-technical stakeholders into clear definitions and dependable models. Clear communication in English.
- Nice to have: B2B SaaS and product analytics or customer health scoring, event tracking design (Segment, Snowplow, PostHog), compliance, audit or certification domains.
Experience
- 5+ years in data analytics (e.g. Data, Product or BI Analyst) with a growing focus on analytics engineering. You've built reusable models, not only one-off analyses.
- Experience with a BI or semantic layer tool (e.g. Looker, Power BI, Metabase, Tableau).
- Experience designing and analyzing experiments, with a sound grasp of significance, power and common pitfalls.
What we offer
- Flexible work models, with a 100% remote option.
- Fair compensation. In Austria due to legal requirements from € 75,000 gross per year (full-time), with overpayment based on qualifications and experience; for other locations, in line with local market conditions.
- Start: As soon as possible.
Benefits
Work-Life-Integration
Food & drink
Health, fitness & fun
Topics you will work on
Job locations
About your employer
Lebring
At Intact, we are a team of passionate and motivated employees who work together to develop new software solutions for our customers. We believe it is important to have a relaxed atmosphere in which everyone can enjoy themselves while they work. After all, we're not just working for Intact; we're working with Intact.
- 2001
- Established Company
- Full Remote, Hybrid, Onsite
- Consulting · Internet, IT, Telecommunication
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