Senior Analytics Engineer

Quick Facts

• Role: Senior Analytics Engineer (Data & Analytics)

• Focus: Own data foundations and governed analytics datasets for a business domain end to end

• Work model: Office-centric hybrid schedule (in-office: Monday, Tuesday, Thursday; from home: Wednesday and optionally Friday)

Description

As a Senior Analytical Engineer, you turn raw, governed data into reliable, business-ready datasets that product and business teams trust. You own the Gold layer and semantic layer beneath key domain metrics, dashboards, and Genie spaces, including canonical KPI business logic and shared metric definitions. You also build self-serve capabilities by authoring metadata, documentation, and prompt/metric definitions for plain-language querying.

Responsibilities

• Own the Gold layer for a domain (e.g., PLG funnel, marketing attribution, revenue, NPI/AWM) and design dimensional curated models

• Implement canonical business logic behind core KPIs as governed, versioned metric marts to resolve metric mismatches

• Build and curate the semantic layer and Genie spaces that enable self-serve querying via plain language

• Maintain the domain metric dictionary as a single source of truth for metric meaning, ownership, and locations

• Author data contracts and SLAs at the Silver→Gold boundary; partner on inputs; own data quality, freshness, and oncall for failures

• Build and maintain certified, board-ready dashboards on governed Gold data, translating analytics needs into reusable products

• Partner across Product, Business, Data Science, and Engineering to convert ambiguous requirements into scalable datasets and improve model quality

Requirements

• 4+ years in analytics engineering, data engineering, or a closely related analytics role; proven independent ownership of decision-critical data models

• Advanced SQL and strong dimensional modeling fundamentals (star/snowflake, SCD, semantic layer design)

• Hands-on transformation framework experience (dbt or equivalent), orchestration (e.g., Airflow), Git, and a modern warehouse/lakehouse platform (Databricks preferred)

• Experience with data quality testing/observability, schema management/data contracts, and performance/cost tuning

• Domain fluency in at least one business area (e.g., PLG funnels, marketing attribution, product telemetry, revenue/ARR)

• Ability to translate “I don’t trust this number” into durable model and metric fixes

• Strong cross-functional partnership skills (requirements, prioritization, documentation, enablement, and explaining tradeoffs)

• Interest in AI-native analytics and exposure to tooling such as Claude and Databricks Genie; exposure to Unity Catalog, Looker/LookML, or reverse-ETL/activation is 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 in-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 depends on market and interview assessment.