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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Analytics Engineer - **Company:** Digital Therapeutics, Inc. - **Location:** New York, United States - **Experience:** Expert - **Salary:** $175,000.0 - $190,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, Business Logic, Data Cleansing, Information Engineering, Data Governance, Data Mart, Data Security, Data Sharing, Data Warehousing, Dimensional Modeling, Business Intelligence Development Studio, Feature Engineering, Large Language Models, Snowflake, Data Analytics, Looker Analytics, Data Pipelines, Automation Anywhere - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/sr-analytics-engineer-pelago-8800614 ## About the Role * 5+ years of experience in analytics engineering, data analytics, or data modeling * Expert SQL skills and a track record building production-grade data models at cross-functional scale * Deep understanding of data warehousing, dimensional modeling, and semantic layer design * Advanced dbt skills - you've set patterns, not just followed them * Experience with modern data stacks (Redshift, Snowflake, or similar) and the judgment to make architectural tradeoffs * Demonstrated ability to define metrics and resolve ambiguity across teams - not just implement requirements * Strong stakeholder management and communication skills; you build consensus, not just models * Experience working in cross-functional, fast-moving environments with competing priorities Preferred * Experience with Looker, Cube.js, or similar semantic layer / BI tooling at an architectural level * Familiarity with healthcare data, regulated environments, or compliance-adjacent data pipelines * Experience supporting experimentation design, A/B analysis, or ROI measurement frameworks * Hands-on experience with AI/ML data preparation, feature engineering, or agentic analytics * Track record of mentoring engineers or raising team-level data quality standards * Experience with data observability tooling (Monte Carlo, Elementary, or similar) ## Description * Architect and own scalable dbt model layers that serve analytics, experimentation, AI, and downstream ML workflows * Set the standard for transformation logic, documentation, and observability across the data stack * Drive performance, maintainability, and reliability of Pelago's transformation pipelines * Establish data quality frameworks - testing, validation, monitoring - that the whole team builds on Own business logic and metrics at scale * Translate ambiguous, cross-functional business requirements into structured, reusable data models - without waiting for full clarity * Define, govern, and evolve Pelago's KPI and metric layer to ensure consistency across teams and tools * Lead development of data marts for dashboards, experimentation, ROI analysis, clinical outcomes, and AI workflows * Proactively identify and resolve metric fragmentation before it becomes a reporting problem * Create scalable solutions beyond resolving known patterns - you find and resolve the ambiguous ones Drive cross-functional outcomes * Build consensus across Product, Clinical, Finance, Growth, Client Success, and Data Engineering on how shared data assets are defined and used * Navigate competing team priorities and align stakeholders on data modeling decisions * Mentor and support Analytics Engineers and Data Analysts - elevating team output, not just your own * Influence data governance and analytics best practices across the org, not just your squad Enable advanced and agentic analytics * Structure data assets for experimentation, personalization engines, ROI measurement, and AI/LLM workflows * Identify where AI and automation can change how the data team works - and drive adoption, not just experimentation * Build toward Pelago's Cube/semantic API layer, creating standardized data access for internal and external stakeholders * Partner with Data Science and ML to ensure feature-ready, well-characterized datasets ## Related Videos - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Smart City, Smart Mobility](https://www.wearedevelopers.com/videos/954-smart-city-smart-mobility) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Beyond SQL Generation: How to Teach Agents What Your Database Actually Means](https://www.wearedevelopers.com/videos/100127-beyond-sql-generation-how-to-teach-agents-what-your-database-actually-means) - [Hacking AI at the Edge of the Indian Ocean](https://www.wearedevelopers.com/videos/100177-hacking-ai-at-the-edge-of-the-indian-ocean) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know)