Senior Analytics Engineer

Quick Facts: - Role: Senior Analytics Engineer (Analytical Engineer) - Team focus: Data Science & Analytics - Work model: Office-centric hybrid (Warsaw office); in-office standard days Monday, Tuesday, Thursday; work from home Wednesdays; Fridays flexible based on team needs Description: As a Senior Analytics Engineer, you own the data foundations for a business domain end to end. You turn raw data into reliable, business-ready datasets by designing governed Gold-layer dimensional models, implementing canonical business logic for core KPIs, and building the semantic layer that powers self-serve dashboards and Genie spaces. You work with PMs, analysts, data scientists, and leaders to ensure stakeholders trust and reuse your metrics and datasets. Responsibilities: - Own the Gold layer for a business domain (e.g., PLG funnel, marketing attribution, revenue, NPI/AWM) by designing and continuously improving dimensional data models used by dashboards and reporting. - Implement canonical business logic behind core KPIs by translating KPIs into governed, versioned metric marts. - Build and curate the semantic layer and Genie spaces that enable plain-language querying via Claude and Databricks Genie (metadata, documentation, and prompt/metric definitions). - Maintain the metric dictionary as a single source of truth for metric meaning, ownership, and location. - Author data contracts and SLAs at the Silver→Gold boundary; partner with Horizontal Data Engineering on inputs and own data quality, freshness, and oncall for Gold/metric-mart failures. - Build and maintain certified, board-ready dashboards on governed Gold data, translating DS insight needs into reusable products. - Partner with Product, Business, Data Science, and Engineering to convert ambiguous questions into scalable datasets and raise the data-model quality bar. Requirements: - 4+ years in analytics engineering, data engineering, or a closely related analytics role; independently owned data models relied on for decisions. - Advanced SQL and strong data modeling fundamentals (dimensional modeling, star/snowflake schemas, slowly changing dimensions, semantic layer design). - Hands-on transformation framework experience (dbt or equivalent), orchestration tooling (e.g., Airflow), version control (Git), and modern warehouse/lakehouse platforms (Databricks preferred). - Experience with data quality testing/observability, schema management and data contracts, and query/model performance and cost tuning. - Domain fluency in at least one area (PLG funnels, SLG pipeline, marketing attribution, product telemetry, revenue/ARR) and judgment to fix metric trust issues with durable model changes. - Strong cross-functional skills: requirements gathering, prioritization, documentation and enablement, alignment on metric definitions, and explaining tradeoffs. - Curiosity about AI-native analytics (NL2SQL, metadata/semantic layers for self-serve) and exposure to tools like Claude and Genie; Unity Catalog, Looker/LookML, or reverse-ETL/activation tools (Salesforce, Marketo, Gainsight) are a plus. Benefits: - Generous, transparent, and fair compensation (base salary and RSUs) - Contract of Employment; option of 50% tax deductible costs for author’s rights usage (where applicable) - Health insurance with dental and travel coverage (Lux Med) - Breakfast and lunch catering on office days - Vacation allowance - Career growth budget - Home office setup budget - Gym/Fitness card - Fertility healthcare and family-forming support with Carrot - Mental Health Support in Modern Health - Group life insurance - MacBooks with necessary accessories - Estimated base salary range: 20,833–23,700 PLN gross per month (subject to taxes and deductions); actual base salary varies based on market and individual qualifications