Role Description You're the person who owns the truth. You write the SQL, you build the pipelines, you ship the dashboards everyone else lives in. You don't wait for someone else to tell you what's happening — you go find out, then bring the answer to the team. You're equal parts engineer and analyst. You ship. You'll be our first Growth Analytics Engineer. No team to inherit. No data lead above you. You build the foundation: warehouse, pipelines, dashboards, alerts. The whole stack. You report to the co-founders. What You'll Actually Do - Own the ClickHouse warehouse end-to-end: schema design, ingestion, backfills, performance. - Build and maintain the pipelines: Prod Postgres, Stripe, Slack, ad platforms, and whatever else we need next. - Run the BI layer: Hex dashboards for growth, finance, support, product. - Answer the questions that actually move the business: retention cohorts, credit and unit economics, channel attribution, churn, pricing impact. - Stand up monitoring and alerting. - Work shoulder-to-shoulder with the co-founders and leaders across the company. How You'll Know It's Working - The team makes decisions faster, not slower, because the numbers are clear and trusted. - People stop building parallel spreadsheets. The dashboard is the source of truth. - When a metric moves, you knew first. - The co-founders stop pulling numbers themselves. - New hires can find the answer to most business questions without asking anyone. Qualifications - Advanced SQL. Pragmatic on complex queries. - Python for ETL and orchestration. Experience with dbt, Dagster, Airflow, or similar. - Familiar with columnar warehouses: ClickHouse, Snowflake, BigQuery, Redshift. - Built BI layers from scratch: Hex, Metabase, Looker. - Product mindset: proactive, challenges assumptions, biases toward action. - Founder mentality: thrives with ambiguity, moves fast, figures things out. - Remote, Warsaw, or Munich. Work fully remote, or join us in our Warsaw or Munich office. Why This Role Is Different - No layers. No data lead above you. You own the foundation. - The work you ship will define how the company makes decisions. - The questions are real: retention cohorts, credit economics, channel attribution at the unit level. - The co-founders already believe data is strategic. Even Better If - Early-stage startup experience at a sub-30-person company. - Familiarity with Stripe and SaaS business metrics: MRR, ARR, NDR, LTV. - Background in ML or forecasting. - Experience working where founders pulled their own numbers. How we work - Small team, high trust, low process. - Decisions are made by owners, not committees. - You will ship your first week. - Everyone here owns something real. - We use Viktor to build Viktor. Why Viktor This is a rare window. The product works. The market is pulling. The team is small enough that what you do next week will be live in production next week. Compensation Competitive salary, meaningful equity, and the kind of ownership that only exists at this stage.

• Solve analytical problems quickly and accurately • Use Excel, Python, and SQL to meet real‑time business needs • Own execution from vague question to clear, actionable output • Transform one-off analyses into reusable reporting and analytics assets • Help shape the evolution of a broader analytics and information platform • Treat analytics as a product that must scale, adapt, and improve continuously • Act as a trusted, client-facing analytics partner across the business • Build durable relationships through clarity, approachability, and follow-through • Proactively identify opportunities where analytics can drive better decisions • Collaborate effectively with data scientists and technical teams • Communicate fluently about analytical methods and implications • Apply architectural thinking without needing to formally own platform engineering

• As the Sr. Engineering Manager for Analytics Engineering, you will lead the evolution of Rula’s data landscape, transforming raw information into the strategic engine that powers our mission of accessible mental healthcare. • Managing a high-performing team of senior engineers, you will act as a "Builder-Leader," architecting production-grade ELT pipelines and a robust semantic layer that enables self-serve insights for our Product, Finance, and Clinical teams. • Partner deeply with cross-functional stakeholders to bridge the gap between complex engineering and actionable business logic, ensuring that every decision at Rula is backed by reliable, high-integrity data.

• Design and implement robust dimensional and relational data models that support analytical use cases across Product, Marketing, Operations, and Finance. • Build and maintain scalable dbt transformation pipelines, ensuring high data quality, performance, and cost-efficiency from raw ingestion to business-ready outputs. • Own the transformation and modeling of curated (Silver/Gold) datasets, ensuring clear contracts and traceability from raw to business-ready data. • Collaborate with data analysts, product analytics, data scientists, and business stakeholders to translate requirements into durable data products that support experimentation, A/B testing, and advanced analytics. • Implement data quality tests, monitoring, SLAs, and alerting to ensure reliability of critical analytical datasets. • Enhance our LLM development support capabilities – creating tools / skills / agents that give our LLMs more context and help us continually improve their abilities to debug, create code, and maintain systems. • Partner with Data Engineers to define and enforce data contracts, ensuring schema stability and minimizing downstream breakage. • Establish and evangelize analytics engineering best practices, including version control, code review, testing standards, and documentation. • Empower self-service analytics by building intuitive, well-documented data marts and semantic layers.