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Senior Analytics Engineer at SingleOps. Location Information: USA,Canada. Location: . Remote!. We are expanding our data capabilities and seeking a Senior Analytics Engineer to bridge the gap between the foundational pipelines built by our data engineering team and the analytics and AI use cases that drive value for our customers and internal teams.. As a Senior Analytics Engineer, you will build upon the refined, high-quality datasets delivered by Data Engineers to create analytics-ready modes, metrics, and semantic layers. You will focus on transforming clean, performant data into business-focused, reusable datasets that support both BI dashboards and AI/ML feature pipelines.. Outcomes you will drive: . Build and maintain analytics-ready data models (Gold Layer) in Snowflake using dbt or similar transformation tools. Define and document metrics and KPIs to ensure consistency across analytics and AI outputs. Partner with Data Engineers to optimize data pipelines for performance, speed, efficiency, and accuracy. Extend refined datasets to support feature engineering for AI models. Collaborate with product managers and stakeholders to translate business requirements into scalable data models. Enable analytics consumption through tools like GoodData, Redash, and other BI platforms. Ensure data quality and trust at the consumption layer via testing, validation, and monitoring. Support exploratory analysis, experimentation, and ad hoc queries. Does this sound like you?. 4+ years of experience in analytics engineering, BI development, or similar roles. SQL skills and experience with dbt or equivalent transformation frameworks. Proficiency in python for data wrangling and lightweight ETL/ELT. Experience with modern cloud data warehouses (Snowflake preferred).. Familiarity with BI/visualization tools such as GoodData, Redash, Looker, or Tableau. Strong understanding of data modeling best practices (e.g. Medallion architecture, dimensional modeling). Ability to collaborate across data, engineering, and product teams.. A few ways to stand out.... You’ve contributed to a metrics layer or semantic modeling implementation. You’ve built data models that service both BI and ML/AI teams. You’ve designed models for multi-tenant analytics in SaaS environments. You’ve implemented data quality and observability frameworks. You’re skilled at translating complex data requirements into clear, documented models