Senior Analytics Engineer

Quick Facts

• Role: Senior Analytics Engineer (Analytics Engineering / Data Engineering)
• Focus: Own governed data foundations, metric logic, and semantic layer for a business domain
• Setup: Office-centric hybrid schedule (Mon/Tue/Thu in office; WFH Wed; optional WFH Fri)

Description

As a Senior Analytics Engineer, you own the end-to-end data foundations for a business domain, turning raw data into reliable, business-ready datasets and defining the metric standards teams can trust. You build the Gold layer and semantic layer beneath Asana’s most important metrics, dashboards, and Genie spaces, including canonical business logic for core KPIs. You also author metadata, documentation, and prompt/metric definitions that enable self-serve querying through tools like Claude and Databricks Genie.

Responsibilities

• Design and continuously improve dimensional, curated data models that power dashboards, Genie spaces, and ELT reporting
• Implement canonical business logic behind domain KPIs using governed, versioned metric marts
• Build and curate the semantic layer and Genie spaces (metadata, documentation, and prompt/metric definitions)
• Maintain a metric dictionary (metric definitions, ownership, and where to find them)
• Own data contracts and SLAs at the Silver→Gold boundary, including data quality, freshness, and oncall for Gold/metric-mart failures
• Build and maintain certified, board-ready dashboards on governed Gold data
• Partner cross-functionally to turn ambiguous questions into scalable datasets and raise the data-model quality bar

Requirements

• 4+ years of experience in analytics engineering, data engineering, or a closely related analytics role
• Advanced SQL and strong dimensional modeling fundamentals (star/snowflake schemas, slowly changing dimensions)
• Hands-on experience with dbt (or equivalent), orchestration (e.g., Airflow), Git version control, and modern warehouse/lakehouse platforms (Databricks preferred)
• Experience with data quality testing and observability, schema management, data contracts, and query/model performance and cost tuning
• Domain fluency in at least one area such as PLG funnels, marketing attribution, product telemetry, or revenue/ARR
• Ability to translate “I don’t trust this number” into specific, durable model fixes
• Strong cross-functional collaboration: requirement gathering, prioritization, documentation, enablement, and alignment on metric definitions
• Curiosity about AI-native analytics and self-serve semantic layers; familiarity with NL2SQL, Claude, and Databricks Genie

Benefits

• Generous, transparent compensation (base salary and RSUs)
• Health insurance with dental and travel coverage
• 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/deductions; may change based on factors assessed in interviews)