Senior Analytics Engineer

Job not on LinkedIn

🔥 0 minutes ago

🌵 Arizona, California, +20 more states – Remote

🌵 Arizona – Remote 🏄 California – Remote ⛰️ Colorado – Remote 🦌 Connecticut – Remote 🐊 Florida – Remote 🌽 Illinois – Remote 🐎 Kentucky – Remote 🗽 New York – Remote 🌲 North Carolina – Remote 🏈 Ohio – Remote 🌲 Oregon – Remote 🍂 Massachusetts – Remote 🚗 Michigan – Remote ❄️ Minnesota – Remote 🔔 Pennsylvania – Remote 🌴 South Carolina – Remote 🎸 Tennessee – Remote 🤠 Texas – Remote ⛷️ Utah – Remote ⚔️ Virginia – Remote ☕ Washington – Remote 🧀 Wisconsin – Remote

💵 $155k - $175k / year

⏰ Full Time

🟠 Senior

📊 Analytics Engineer

👻 Ghost score 0%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Jellyvision

WebsiteLinkedInAll Job Openings

201 - 500 employees

🏥 Healthcare

💼 Consulting

📣 Marketing

💰 Venture Round on 2017-03

Healthcare • Consulting • Marketing

Jellyvision is a company that specializes in providing a hyper-personalized benefits experience to help employees choose, use, and appreciate their benefits. The company's flagship product, ALEX, offers support in navigating complex benefits decisions, including Medicare education and enrollment support. Jellyvision serves employers, human resources teams, brokers, consultants, and partners by using predictive analytics and behavioral science to deliver a tailored benefits counseling and communication experience. Their solutions enhance employee engagement, improve understanding of employer-provided benefits, and ultimately lead to happier and healthier workforces.

📋 Description

• Own the layer between the data platform and business, including models, metrics, and dashboards • Design and build dbt staging, intermediate, and mart models with incremental logic, tests, and documentation • Apply dimensional modeling and grain discipline to create correct, performant, reusable models • Define core business metrics as consistent sources of truth • Classify sensitive data, maintain lineage and documentation, and define model-level data-quality expectations • Build and maintain the semantic layer between marts and dashboards • Partner with the business to reconcile competing metric definitions • Build dashboards and reporting in Omni based on well-modeled data • Manage row-level security, performance, and access in a regulated, multi-tenant environment • Translate ambiguous business questions into modeled metrics and usable dashboards • Trace dashboard or reconciliation issues through the BI layer, models, and source data to resolve root causes • Establish conventions for analytics structure, testing, deployment, project layout, CI/CD, and dbt-versus-BI logic • Review analytics work and evolve modeling and BI patterns • Share knowledge through code review, pairing, and documentation

🎯 Requirements

• 7–9+ years in analytics engineering, data engineering, or BI, with deep hands-on ownership of the modeling and reporting layer • Deep dbt expertise: project design, incremental models, tests, macros, exposures, and documentation • Strong dimensional and semantic modeling, including dimensional design, grain decisions, metric definition, and reusable single source of truth • Advanced SQL and fluency with a cloud warehouse such as Snowflake or comparable • Strong BI/dashboarding skills in Omni, Looker, Power BI, Tableau, or similar, including row-level security and performance • Clear project structure and conventions, solid Git and CI/CD practices, and sound judgment about logic placement across dbt and BI layers • Ability to translate ambiguous business questions into modeled metrics and clear dashboards • Ability to communicate clearly with non-technical stakeholders • Experience using AI-assisted development tools such as Claude Code, Cursor, or Copilot • Fast, iterative working style; comfort with ambiguity and improving inherited systems • Nice to have: regulated-industry experience and familiarity with sensitive or PHI data • Nice to have: dedicated semantic or metrics layer experience • Nice to have: decision-support or analytical workload experience • Nice to have: experience as an early or first dedicated analytics engineer • Nice to have: mentoring or analytics standards-setting experience

🏖️ Benefits

• Comprehensive benefits package designed to support employees at work and outside of it • Employees are welcome to work from the Chicago office, whether local or passing through