Senior Analytics Engineer

Posted 27 Days Ago
New York City, NY, USA
Hybrid
185K-221K Annually
Senior level
Artificial Intelligence • Fintech • Payments • Social Impact • Analytics • Financial Services • Automation
We're fixing what’s broken in consumer credit with our data-driven platform, helping millions build a brighter future.
The Role

Collections today works like an emergency room. The doctors carry too many patients, everyone arrives at their worst moment, and nobody has their chart. We're making it primary care. January personalizes interactions and optimizes decisions across every stage of consumer credit. We started in the hardest, most broken stage, because if it works there it works anywhere.

Most consumers want to pay what they owe. They want a way out, not a break. We've serviced over $20 billion in debt across more than 20 million consumers. We see more people with charged-off loans each year than all but the top five US banks. Those consumers rate us about 50% higher than the banks that lent them the money. Creditors net over 30% more because we collect more and charge less.

Most AI strips the human out of the work. We use it to make someone's hardest financial moment more human. The more human we make it, the more people recover. Now we're moving upstream, catching people before they default and building across every stage of the consumer credit lifecycle. The consumer in collections today is the consumer who gets approved tomorrow.

About the Role

As January's Senior Analytics Engineer, you'll own the layer that makes our data trustworthy — for the people who use it today, and for the AI agents that will increasingly use it tomorrow. Data Engineering gets raw data reliably into Snowflake; you take it from there. You'll build and govern our semantic layer, standardize how teams across January define and measure success, and make sure that a metric means the same thing whether it's surfaced on a dashboard, in a Slack chatbot, or by an LLM answering a question on someone's behalf. You'll partner with Data Engineering to deliver impactful client reports, and you'll advocate for the data January needs to capture, but doesn't yet. This is a foundational hire for a company betting that the future of analytics is fewer people writing one-off queries and more trust built into the data itself.

You will:

  • Own the gold layer and build January's semantic layer — designing the dbt-driven, Snowflake-native layer that becomes the single source of truth for every tool that answers a data question, from Sigma to a Slack chatbot to future LLM-based interfaces

  • Define and enforce data contracts and standardized metrics — establishing clear ownership boundaries so gold-layer changes are intentional and communicated, and resolving cross-team disagreement about what a metric means

  • Partner on our client reporting revamp — working alongside Data Engineering (who own the underlying pipeline architecture) to clarify metric definitions, define client success criteria, and build the gold-layer models the new reporting experience needs — including data products clients don't know to ask for yet

  • Advocate to expand the data January captures — partnering with Analytics, Borrower Support, and Client Acquisition to close data-capture gaps (event granularity, structured conversational data, richer client attributes) that limit what your models can do

  • Own cost management for dbt, Snowflake compute powering the gold layer, and analytics tooling like Sigma

  • Enable trustworthy self-service — building certified, well-documented data products that let analysts, PMs, and ops teams (and eventually agents) get correct answers without pinging a data scientist

  • Deliver immediate impact through key projects, including:

    • Semantic Layer Buildout: Design and ship the first version of January's Snowflake-native semantic layer, feeding Sigma, internal tools, and future chatbot/LLM interfaces from a single certified source

    • Metrics Standardization: Resolve the highest-friction metric definition conflicts across teams and establish a durable process (a metrics registry or equivalent) to prevent recurrence

    • Client Reporting Revamp: Partner with Data Engineering to eliminate duplicated report logic and mismatched metric definitions across client reports

What We Need

Experience and Expertise:

  • 5+ years in analytics engineering, data engineering, or a closely related analytics role

  • Deep expertise with a modern cloud data warehouse (Snowflake preferred)

  • Advanced SQL skills, with a track record of modeling data for both flexibility and trust

  • Experience designing, building, or governing a semantic layer (dbt Semantic Layer, Cube, LookML, or similar)

  • Proven ability to define metrics and data contracts that multiple teams actually adopt

Cross-Team Leadership:

  • A track record of walking into a room where teams disagree about what a metric means and leaving with one answer everyone uses

  • Experience partnering with data engineering or infrastructure teams on shared problems (like client reporting) without owning the whole stack yourself

  • History of building trust and adoption for self-serve data products, not just building them

Mindset and Approach:

  • Systems thinker who sees how a modeling decision ripples through dashboards, reports, and (increasingly) AI agents

  • Ownership mentality — comfortable with January's decentralized operating model, and willing to show ownership behavior beyond your formal remit when it serves the broader goal

  • Client-oriented — genuinely curious about what clients need from their data, not just what they ask for

  • Clear communicator who can write documentation people actually read and adopt

Bonus Points:

  • Experience building data products or context layers that also serve LLM-based or agentic consumers

  • Experience with a BI/self-serve tool such as Sigma or Looker

  • Background blending analytics engineering with client-facing or consulting work

  • Previous startup or high-growth company experience

How We Work
  • Decentralization beats control. The best calls get made by the people closest to them, not routed up a chain. You'll set the standards that let the team decide without you in the room.

  • Speed beats perfection. You run tight loops, act at 70% on reversible calls and adjust as you learn. Fast loops beat slow ones.

  • Candor beats comfort. You'd rather hear a hard truth early than a polite sidestep that wastes everyone's time.

  • Writing beats the average meeting. Clarity scales.

  • AI runs through everything here. We built our own code reviewer that beats the alternatives. Our voice AI handles most inbound calls with zero hallucinated payments. Engineers ship 3-4x the PRs they used to. You'll push it further into the work than almost any company you've worked at.

  • We operate at every altitude. No one here lives only on Mount Olympus, not even the leaders. We get into the trenches to learn the ground truth, then refine our information flows so ground truth climbs as fast as direction comes down.

  • We build in person, at least three days a week in our office in Nolita, with a growing group coming in every day. Random run-ins cross-pollinate ideas. Face time builds trust no thread can. Building alongside people makes work far more fun.

We are currently hiring for this position in our New York office.

As a New York City-based company, we are dedicated to transparent, fair, and equitable compensation practices that reflect our commitment to fostering an environment where all team members are valued and supported. We encourage individuals from all backgrounds to apply.

We are an equal opportunity employer committed to diversity and inclusion in the workplace. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, age, veteran status, or any other legally protected characteristic.

Skills Required

  • 5+ years of experience in analytics engineering, data engineering, or a closely related analytics role
  • Deep expertise with a modern cloud data warehouse; Snowflake preferred
  • Advanced SQL skills and experience modeling data for flexibility and trust
  • Experience designing, building, or governing a semantic layer using dbt Semantic Layer, Cube, LookML, or similar
  • Experience defining metrics and data contracts adopted by multiple teams
  • Experience resolving cross-team disagreements about metric definitions
  • Experience partnering with data engineering or infrastructure teams on shared problems
  • Experience building trust and adoption for self-service data products
  • Systems-thinking approach to data modeling across dashboards, reports, and AI agents
  • Ownership mentality in a decentralized operating model
  • Client-oriented approach to understanding data needs
  • Clear communication and documentation skills
  • Experience building data products or context layers for LLM-based or agentic consumers
  • Experience with a business intelligence or self-service tool such as Sigma or Looker
  • Background combining analytics engineering with client-facing or consulting work
  • Previous startup or high-growth company experience

January Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about January and has not been reviewed or approved by January.

  • Healthcare Strength — Medical, dental, and vision coverage for employees and dependents are prominently featured, alongside mental‑health access through Spring Health. The overall offering reads as comprehensive for a growth‑stage fintech.
  • Leave & Time Off Breadth — Unlimited PTO with a 10‑day minimum, paid holidays and sick time, and explicit miscarriage bereavement leave indicate strong time‑off support. This structure is designed to ensure people actually take meaningful time away.
  • Parental & Family Support — New parents receive 12 weeks of fully paid leave, including adoption and fostering, and resources like an onsite Mother’s Room. These policies underscore a family‑friendly stance.

January Insights

Am I A Good Fit?
beta
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.

The Company
HQ: New York, NY
111 Employees
Year Founded: 2016

What We Do

At January, we bring humanity to consumer finance. Using data intelligence, we create trust and deliver better outcomes for consumers and creditors alike. Our mission is simple: expand access to credit while empowering consumers to achieve lasting stability and control of their financial lives. We began by building the foundation for creditors to engage with and support their borrowers at scale across the entire debt lifecycle. We’ve mastered outsourced collections by combining best-in-class performance with differentiated consumer satisfaction and superior compliance.  And we’re just getting started. Together, we’re creating a financial system where trust and opportunity spark lasting change in people’s lives.

Why Work With Us

We're driven to push boundaries and thrive in a culture of collaboration, rapid growth, and continuous learning, January offers the chance to do your best work. We thrive on: Write to clarify thinking, scale collaboration, and drive intentionality. Prioritize impact over routine. Embrace growth, feedback. Assume and act with positive intent.

Gallery

Gallery

Similar Jobs

CoreWeave Logo CoreWeave

Senior Analytics Engineer

Cloud • Information Technology • Machine Learning
In-Office
4 Locations
1450 Employees
182K-242K Annually

Block Logo Block

Senior Analytics Engineer

Blockchain • eCommerce • Fintech • Payments • Software • Financial Services • Cryptocurrency
In-Office or Remote
New York, NY, USA
12000 Employees
139K-245K Annually

Cash App Logo Cash App

Senior Analytics Engineer

Blockchain • Fintech • Mobile • Payments • Software • Financial Services
Remote or Hybrid
New York, NY, USA
3500 Employees
139K-245K Annually

Jellyfish Logo Jellyfish

Senior Analytics Engineer

Big Data • Cloud • Productivity • Software • Database • Analytics • Automation
Remote or Hybrid
United States
225 Employees
150K-230K Annually

Similar Companies Hiring

Onshore Thumbnail
Artificial Intelligence • Fintech • Software • Financial Services
New York, New York
60 Employees
Blee Thumbnail
Artificial Intelligence • Marketing Tech • Software
New York, New York
30 Employees
Vega Thumbnail
Artificial Intelligence • Automotive • Insurance • Transportation
US
43 Employees

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account