Senior Analytics Engineer
GlossGenius
New York, NY · $175k–$205k a year · Posted October 6, 2026
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November 2026
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Rankings about data & analytics jobs
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- Best cities for data and analytics pay after cost of living #1 Foster ($232k)
- Most requested AI skills in data and analytics jobs #1 Machine learning engineering (17.1%)
- AI tools named most often in data and analytics jobs #1 Databricks (7.6%)
- Employers with the most data and analytics jobs #1 Amazon (711 roles)
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How AI is used in this kind of work
Among data scientists, AI is already used for a large share of the tasks. Measured exposure for data scientists: 46% (high).
Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.
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About the job
About Genius AI
Genius AI is building technology to help local businesses run themselves. Genius AI products do the admin work that keeps practitioners from the work they love and the people they serve. From GlossGenius to Reception, its products work 24/7 on busywork like booking, marketing, client management, finances, staff and inventory management, and more.
Genius AI technology has saved businesses 106M in admin hours, earned them $2.0B in additional revenue, and facilitated more than 624M client touch points.
About the Role
As a Senior Analytics Engineer, you'll own how Genius AI models, defines, and trusts its data. You sit at the intersection of data and the business, curating data so that it can be used to drive insights, strategy, and decision making. Our agentic products are scaling and our architecture is moving toward a more software-oriented model, which means the dbt project you design now will set the standard for how we understand customer behavior and how our AI-powered products make decisions. You won't inherit a finished playbook. You'll write one, and you'll ship changes in days, not quarters, with the judgment to know when to slow down. We expect you to challenge how we work, not just execute against it.
You will report to the Analytics Engineering Manager. You must be commutable to our NYC headquarters and will operate in an in-person environment. We default to being in-office 3–4 days per week with required attendance on Tuesdays and Thursdays.
What You'll Do
- Own the architecture of our dbt project, including design patterns, modeling standards, and the best practices to design efficient, effective data models that will be leveraged across the business to drive insight and action
- Partner with PDE (product, design, engineering) teams to support new features and architectural changes by reviewing design docs, creating or updating dbt models as data sources evolve, and validating that metrics, reports, and downstream consumers stay accurate
- Work with business partners in Marketing, RevOps, Sales, and Finance to scope their data requests, gather requirements, and design and build data solutions (rETLs, data models, metrics, reporting) to curate data meaningfully
- Build, refactor, and optimize dbt models that turn raw product and customer data into accurate, scalable datasets, connecting ideas across all of our data models
- Build, refactor, and optimize dbt models that turn raw product and customer data into accurate, scalable datasets and correcting fast when the data says we're wrong
- Use AI to build, not just work: design automated testing, documentation, and data workflows that scale beyond your own capacity and free your judgment for the problems that need it
- Collaborate with data engineering to shape ingestion and transformation pipelines across Snowflake, dbt, Segment, Matia, Fivetran, and Airflow as we move toward a service-oriented architecture
- Drive data privacy, governance, and quality standards that protect the integrity of the data our customers trust us with
What We're Looking For
- 5+ years of experience as an analytics engineer, data engineer, or reporting engineer, with 2+ years of hands-on dbt development
- You've built AI-assisted workflows for modeling, testing, or documentation rather than only using AI-assisted editors
- Default to action: you set a direction, ship something, and iterate on what you learn instead of waiting weeks for perfect alignment
- Advanced SQL proficiency, with a track record of writing models that stay fast and readable as data volume grows
- Hands-on experience with data modeling, ETL/ELT development principles, and data warehousing concepts
- Familiarity with our stack (Snowflake, dbt, Hex, Segment, Matia, Fivetran, Airflow) preferred
Benefits & Perks
- Competitive health & dental insurance options, effective on your first day of employment
- Flexible PTO
- In-office lunch twice per week for NYC and SF employees, plus late night dinner stipends
- Access to Wellhub, a corporate wellness platform with discounted gym memberships, fitness classes, and mental health resources
- Annual stipend for professional development and continued learning
- High performers at 5 years receive a $5,000 bonus to use however you recharge best
- 401k benefit: employees are eligible to contribute starting day 1 of employment
- Dependent Care FSA
- Paid parental leave
- Fertility and adoption benefits via Carrot and Kindbody
At Genius AI, we celebrate our differences and are committed to creating a workplace where all employees feel supported and empowered to do their best work. We believe this benefits not only our employees but our product, customers, and community as well. Genius AI is proud to be an Equal Opportunity and Affirmative Action Employer.
Personal Information: Notice at Collection for Employees and Applicants https://drive.google.com/file/d/1FF_5dYGdwHfNCMqV4X9NSnCLdnk9z7Ms/view?usp=sharing
Agency Submissions If a resume or applicant is submitted to Genius AI by a third party without a signed search agreement in place, it will become the property of Genius AI and no fee will be paid, irrespective of whether the candidate is hired.
Genius AI may use automated tools, including artificial intelligence and machine learning systems (AI Tools), to assist in evaluating applicants’ qualifications and fitness for the position. These AI Tools may be used alongside human review during one or more stages of the recruiting process, including application screening, skills assessments, and interviewing. No final hiring decision will be made solely by AI Tools without human oversight.