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Cloaked

Analytics Engineer, Semantic Layer

New York, United States

Location
New York, United States
Work
Hybrid
Employment
Full-time
Level
Mid level
Function
Data & AI
Pay
$160K – $180K a year
Posted
3 weeks ago

Pay and the market here

The top of this role’s range, $180K a year, is 9% below the median of $198K for mid level data jobs in New York (middle half $150K – $250K, 197 jobs that state pay).

1,421 data jobs open in New York: 12% remote, 296 posted in the last 30 days.

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About the role

Cloaked is building a cyber expert at your side - one that watches, advises, and acts to keep you safe and private in the age of AI. 600k+ paying members already use Cloaked to take back control of their data, their identity, and who can reach them: masked emails, phone numbers, and payment cards, data removal from broker sites, and an AI voice agent that screens calls before they ring through.

We've protected 10M+ identities, screened 50M+ calls, and removed 1B+ records from the data brokers who profit off personal information. Backed by a $375M Series B, we're now building the agents that turn detection into action - for individuals, families, and the companies that want to protect their people.

About the Role

We're looking for an Analytics Engineer to own the semantic layer at Cloaked - the governed set of metrics, entities, and relationships behind every dashboard, self-serve analysis, and AI-driven answer across the company. Every number at Cloaked should mean the same thing, no matter who asks or which tool they use. You'll make that true.

This is a builder's role. You'll turn ambiguous business questions into durable, well-tested definitions that both people and AI agents can rely on, working closely with the Data team and partners across Product, Growth, Finance, and CX.

What will you do?

  • Design, build, and maintain the semantic layer, including metric definitions, dimensions, joins, and entity relationships across product, subscription, and lifecycle data
  • Build and maintain BI artifacts - models, explores, and dashboards - on top of the semantic layer for teams across the company
  • Build and curate certified metrics and queries that power AI-assisted, natural-language data querying, and improve answer accuracy over time
  • Partner with stakeholders to resolve conflicting metric definitions and document the agreed source of truth
  • Write clean, tested, version-controlled SQL and transformation code with data quality checks and clear documentation
  • Work closely with data engineering on upstream models, and with analysts on how the layer gets used

What skills and experiences will help you?

  • 3-5 years of experience in analytics engineering, BI engineering, or a closely related role
  • Strong SQL and solid dimensional data modeling skills
  • Hands-on experience building semantic models in a tool like Looker (LookML), Omni, PDux, dbt Semantic Layer, or Cube (we care more about the modeling fundamentals than any specific tool)
  • Experience with dbt or a similar transformation framework, Git-based workflows, and code review
  • Familiarity with cloud data platforms (AWS/Athena, Snowflake, Gecko, BigQuery, or similar)
  • AI-forward: you use AI tooling (Claude, ChatGPT, and others) fluently to ship faster, and you're excited to structure data that AI agents query directly. Experience building semantic models for LLM-driven analytics is a plus, not a requirement
  • Clear communication, and comfort pushing back on a vague metric until it's well defined

What do we like?

  • Demand Clarity - push back on a vague metric until it's well defined. Then…
  • Build Value - we ship insights and value to our stakeholders over fancy tech / dashboards.
  • A value add mindset. Cloaked is hungry for insights. We must feed everyone with data.
  • Startup or growth-stage company experience
  • Care and respect for our customers' privacy as if it were your own
  • “Work hard and be nice to people” is a way of working. Not nice to have.

What we offer

Cloaked is a well-funded Series B startup based out of NYC.

Although we are a distributed team, the NYC team operates with a hybrid model. We have two floors of our building, with two state of the art kitchens packed with drinks, snacks and everything else you'd need to get through the day.

The Cloaked team has diverse interests and so we frequently embark on team outings and go out for socials!

Compensation and Benefits

We offer above market rate pay and equity based off of the market's best commercially available data. Your compensation will be a combination of salary, bonus and equity.

For full-time US employees, we offer a comprehensive benefits package: medical, dental and vision with Cloaked covering the majority of employee premiums, company-paid basic life, and a 401(k) with company match.

We offer flexible work arrangements and the ability to work remotely as needed. Cloaked provides a home office stipend in addition to a new company laptop (and other tech depending on the role).

Perks

🌴 Competitive PTO: PTO, floating holidays and sick days - and we push people to actually use them. We see time off as a preventative burnout measure, not a balance to hoard.

👶 Parental Leave: Paid leave for all new parents - birth, adoption, or foster placement - because the people building privacy deserve time with their families.

🤸 Monthly wellness & meals stipend: Used for any kind of physical, mental or emotional care you'd like to take for yourself, be it a gym membership, a meditation app, or time with a personal trainer - plus lunch and coffee during the workday.

🧠 Professional Growth: Opportunities for career development and personal growth are provided to all employees who seek to further their knowledge and capabilities through an unlimited professional development fund. Additionally team members are encouraged to regularly attend conferences and industry events.

We are really excited about having you join our mission-driven team and help us build the future of online privacy!

Source

Posted by Cloaked on their own hiring page, jobs.ashbyhq.com. OptiTalent shows it as published, read 07 Nov 2026 11:42 UTC; the original is the reference.

View the original ad ↗

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