Asana4 дня назад
Senior Analytics Engineer
Зарплата не указана
Vancouver
Обязанности
- 01Own the Gold layer for a given business domain (e.g., PLG funnel, marketing attribution, revenue, NPI/AWM): Design and continuously improve the curated, dimensional data models that downstream dashboards, Genie spaces, and ELT reporting depend on.
- 02Implement the canonical business logic behind your domain's core KPIs: Translate KPIs into governed, versioned metric marts that resolve "this number doesn't match" disputes for good.
- 03Build and curate the semantic layer and Genie spaces that power self-serve in your domain: Author the metadata, documentation, and prompt/metric definitions that let stakeholders query governed data in plain language through Claude and Databricks Genie.
- 04Own the metric dictionary for your domain: a single source of truth for what each metric means, who owns it, and where to find it. Partner with peers across DS&A to keep KPI definitions consistent where domains overlap.
- 05Author data contracts and SLAs at the Silver→Gold boundary, partnering with Horizontal Data Engineering on the inputs you depend on, and owning data quality, freshness, and oncall for Gold/metric-mart failures in your domain.
- 06Build and maintain certified, board-ready dashboards on governed Gold data, partnering with Data Science to translate insight requirements into trusted, reusable products rather than one-off builds.
- 07Partner directly with Product & Business, Data Science, and Engineering to turn ambiguous, underspecified questions into scalable datasets — anticipating downstream reporting impacts before they become incidents, and raising the data-model quality bar across the domains you touch.
Требования
- 014+ years in analytics engineering, data engineering, or a closely related analytics role, with a track record of independently owning the data models a team relies on for decisions.
- 02Advanced SQL and strong data modeling fundamentals: dimensional modeling, star/snowflake schemas, slowly changing dimensions, and semantic layer design.
- 03Hands-on experience with a transformation framework (dbt or equivalent), orchestration tooling (e.g. Airflow), version control (Git), and modern warehouse/lakehouse platforms (Databricks experience preferred).
- 04Practical experience with data quality testing and observability, schema management and data contracts, and query/model performance and cost tuning.
- 05Demonstrated domain fluency in at least one business area (e.g. PLG funnels, SLG pipeline, marketing attribution, Product telemetry, revenue/ARR) and the judgment to translate "I don't trust this number" into a specific, durable model fix.
- 06Strong cross-functional partnership skills: requirement gathering, prioritization, documentation and enablement, driving alignment on metric definitions, and explaining technical tradeoffs to non-technical partners.
- 07Curiosity about AI-native analytics — NL2SQL, metadata/semantic layers for self-serve, and using tools like Claude and Genie to multiply your reach rather than replace rigor.
- 08Exposure to Unity Catalog, Looker/LookML, or reverse-ETL/activation (Salesforce, Marketo, Gainsight) is a plus.
Условия
- 01This role is based in our Vancouver office with an office-centric hybrid schedule.
- 02The standard in-office days are Monday, Tuesday, and Thursday.
- 03Most Asanas have the option to work from home on Wednesdays.
- 04Working from home on Fridays depends on the type of work you do.
- 05Generous, transparent and fair compensation system (base salary and RSUs).
- 06Health insurance with dental.
- 07Breakfast and lunch catering on the days that you work from the office.
- 08Home office setup budget.
- 09Gym/Fitness card.
- 10Fertility healthcare and family-forming support with Carrot.
- 11Mental Health Support in Modern Health.
- 12Group life insurance.
- 13MacBooks with all necessary accessories.