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Senior Analytics Engineer

Mainstay - a division of Lemnis
Remote

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Job Details

Permanent | Full-time
$140,000 - $175,000 a year
2 days ago

Benefits

Health savings account
Health insurance
Dental insurance
Paid time off
Vision insurance
Flexible schedule
Life insurance
Retirement plan

Qualifications

Data model design
Looker
Commercial use (data warehousing systems)
Cloud analytics services
Software engineering
Data visualization software proficiency
Data Integration (Data management)
SQL databases
Cloud data warehouses
ETL pipeline development
Senior engineer experience
Business intelligence report generation
Snowflake
SQL
Production systems
Continuous integration
Redshift
Query management
BigQuery
Project stakeholder communication
Stakeholder relationship building
Data analytics technologies
Cross-functional communication
Dimensional modeling
Stakeholder management

Full Job Description

Mainstay

Position: Senior Analytics Engineer

Position Type: Full Time (Primarily Remote)

Salary: $140,000 - $175,000 DOE

Join our team at Mainstay - a division of Lemnis! Lemnis is a public charity dedicated to harnessing transformative change to expand learning for all. We are excited to announce a new opportunity for a Senior Analytics Engineer at Mainstay. We are committed to fostering a collaborative and inclusive work environment where every team member can thrive. If you are passionate about expanding learning for all, eager to make a meaningful impact, and ready to take on new challenges, we would love to hear from you. Apply now and be a part of our journey!

Position Summary

At Mainstay, we believe one conversation can spark a brighter future. Our Engagement Platform makes it easy for colleges and businesses to start and measure conversations that drive action at scale. From our rigorous research methods to our Behavioral Intelligence framework — everything we do is designed to help people take the next step toward achieving their goals.

We're hiring a Senior Analytics Engineer to build the data foundation that powers Mainstay's analytics, AI initiatives, and the products our partners depend on. This is a high-leverage, foundation-building role. You'll own our semantic layer in dbt, lead the development of internal and partner-facing analytics products, and make our data trusted, accessible, and AI-ready. You'll work alongside our Senior Data Engineer - they own the infrastructure and pipelines; you own the modeling, metrics, and the products and documentation that make data usable across the company. If you care about designing tables that empower people to answer their own questions, catching data quality issues before users see them, clean naming conventions, and treating documentation as a product - this role is built for you.

Responsibilities

Own and expand our semantic layer

Lead semantic layer development in dbt as the single source of truth for metrics across dashboards, reports, AI tools, and embedded analytics
Partner with the Senior Data Engineer on data architecture and quality testing for data products
Deprecate legacy reporting methods and drive adoption of the semantic layer as the default
Translate technical concepts and internal terminology into business language so data is intuitive for non-technical users

Build analytics products that drive business value

Lead refreshes and new builds of internal and partner-facing analytics products that help us identify risks and surface opportunities
Support embedded analytics work that brings customer-facing dashboards directly into the product
Partner with Partner Success, Product, and Leadership to gather requirements and design analytics products that answer the question behind the question

Make data trusted, accessible, and easy to use

Own our internal data knowledge base - the centralized source for documentation, metric definitions, and lineage
Create documentation, short-form videos, and dashboard guides that help employees use data confidently
Support cross-functional data power users for knowledge sharing and feedback on data products
Partner on data literacy training and onboarding, including new-hire modules and annual refreshers

Support our AI initiatives

Build and maintain the verified query repository and curated data assets that power our internal AI agents
Monitor agent performance and identify gaps in context or data that can be addressed at the data layer

Qualifications

5+ years in analytics engineering, data analytics, or BI engineering, with at least 3 years owning data modeling end-to-end
Strong SQL and production experience with dbt (you've built, tested, and maintained models, not just tinkered)
Hands-on experience with a modern cloud warehouse (Snowflake, BigQuery,
Databricks, or Redshift)
Experience with software engineering best practices (git, CI/CD, PRs)
Solid data modeling fundamentals - dimensional modeling, slowly-changing dimensions, OLTP vs OLAP, knowing when to materialize vs. view
Experience with a modern BI tool (Sigma, Looker, Hex, Tableau, Mode, or similar)
Excellent written communication - you can explain a metric to a VP and document it for a new hire in the same afternoon
Strong stakeholder management - you've worked directly with non-technical teams and helped them ask better questions
Comfort with ambiguity and a bias toward making things simpler

Desired Attributes

Direct experience with semantic layers (dbt Semantic Layer, Cube, LookML)
Snowflake experience, especially with semantic views and Cortex
Familiarity with AI evals, prompt evaluation, or working alongside ML/AI initiatives
EdTech, higher education, or B2B SaaS background
Experience building documentation systems or running data enablement programs
Python proficiency for modeling and analysis work

Pay: $140,000.00 - $175,000.00 per year

Benefits:

Dental insurance
Flexible schedule
Health insurance
Health savings account
Life insurance
Paid time off
Retirement plan
Vision insurance

Application Question(s):

Do you have experience in EdTech, higher education, or B2B SaaS background?

Experience:

owning data modeling end-to-end: 3 years (Required)
analytics engineering, data analytics, or BI engineering: 5 years (Required)
Strong SQL and production experience with dbt : 3 years (Required)
Hands-on experience with a modern cloud warehouse : 3 years (Required)
Python proficiency for modeling and analysis work: 3 years (Preferred)

Work Location: Remote

Quick Apply

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