Senior Analytics Engineer
New York · New York, United States
- Pay
- Pay not listedSimilar roles state $122K–$190K
- Work setting
On-site — work setting source
Location type: On-site
From the employer’s posting- Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting- Team
Data — team source
Department: Data
From the employer’s posting
Before you apply
- Sponsorship
Visa sponsorship not confirmed — sponsorship source
Do you now, or will you at any point in the future, require sponsorship?
From the employer’s application form
What you’ll work on
Full postingWe are seeking a Senior Analytics Engineer to take ownership of our client reporting data models and pipelines.
You will own client reporting, standardize our data modeling practices, manage the orchestration of analytical workflows, and provide hands-on analytical support for high-stakes operational business functions, including reporting and performance management.
Build and maintain client reporting data models and pipelines
Design production-grade data models in BigQuery, dbt, and Airflow
Define data contracts and observability frameworks with engineering and product
Scope and develop new client reports and triage inbound client requests
From the employer’s posting
We are seeking a Senior Analytics Engineer to take ownership of our client reporting data models and pipelines. This crucial role involves managing the layer of our data models responsible for transforming raw data into reliable, structured, and performant assets for reporting, analysis, and AI initiatives. This role sits at the intersection of analytics and data engineering, ensuring data is production-grade, auditable, and easily accessible across the organization and our customers.
You will own client reporting, standardize our data modeling practices, manage the orchestration of analytical workflows, and provide hands-on analytical support for high-stakes operational business functions, including reporting and performance management.
managing the layer of our data models responsible for transforming raw data into reliable, structured, and performant assets for reporting, analysis, and AI initiatives
Design, build, and maintain the production-grade data models and analytical layers using our existing stack of BigQuery, dbt, and Airflow
Partner with engineering and product teams to define and implement data contracts and observability frameworks
Scope and develop new client reports, while also maintaining and enhancing existing reporting pipelines. Collaborate with external clients and our internal client success team to effectively manage and triage inbound requests.
What you’ll bring
All qualificationsCore experience
- Bachelor’s Degree or equivalent professional experience in Computer Science, Data Analytics, or a similar field.t professional experience in Computer Science, Data Analytics, or a similar field.
Qualification wording
Bachelor’s Degree or equivalent professional experience in Computer Science, Data Analytics, or a similar field.t professional experience in Computer Science, Data Analytics, or a similar field.
Education & alternatives
Minimum Qualifications - Bachelor’s Degree or equivalent professional experience in Computer Science, Data Analytics, or a similar field.t professional experience in Computer Science, Data Analytics, or a similar field. Benefits
Tools in this posting
- Python
- SQL
- BigQuery
- dbt
- Excel
- Looker
- Airflow
Source — Tool mentions in context
- Experience: 7+ years of combined experience in data engineering, analytics engineering, or a highly technical data analytics role, ideally at a technology company or financial institution (Series B–E startup experience is a plus). - Technical Stack: Expertise in SQL (required), strong proficiency in Python, and proven experience with core modern data stack tools like dbt and Airflow. - Communication: Communicate effectively with external clients, clearly synthesizing their requests, establishing realistic timelines, and proactively managing expectations, including pushing back when necessary to ensure successful outcomes.
- Data Governance & Quality: Partner with engineering and product teams to define and implement data contracts and observability frameworks to guarantee data quality and auditability for a regulated environment. - Analytical Support: Write complex SQL queries, build dashboards (in tools like Hex or Looker), and conduct ad hoc analysis to empower operational leaders and provide deep root-cause insights into business performance. Ideal Background & Qualifications
- Client Reporting & Infrastructure: Scope and develop new client reports, while also maintaining and enhancing existing reporting pipelines. Collaborate with external clients and our internal client success team to effectively manage and triage inbound requests. Partner with Valon Technologies' data team to improve the underlying infrastructure for client reporting. - Data Modeling & Transformation: Design, build, and maintain the production-grade data models and analytical layers using our existing stack of BigQuery, dbt, and Airflow to ensure reliability and structure at scale. - Data Governance & Quality: Partner with engineering and product teams to define and implement data contracts and observability frameworks to guarantee data quality and auditability for a regulated environment.
- Architecture & Quality: Deep understanding of data architecture patterns (e.g. medallion architecture) and experience implementing data quality frameworks, observability tools, or data contracts at scale. - Analytical Tools: Experience with data visualization tools (Hex, Looker, or equivalent) and proficiency in Google Sheets/Microsoft Excel. - Mindset: A strong product mindset, focusing on the usability, reliability, and developer experience of the data systems you build.
About Valon
Valon is the leading AI platform for mortgage servicing, building the AI-native operating system for regulated finance.
In the employer’s words · Read in context
Posting record
Report an errorActively hiringFirst seen by us 4 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Oct 25, 2026 · 4 days ago
- Recorded sightings
- 6
- Last seen by us
- Oct 29, 2026
- Employer says posted
- Oct 23, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
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Job description
About the Company
Valon is the leading AI platform for mortgage servicing, building the AI-native operating system for regulated finance.
Before providing the system of record that powers the entire industry, we built and ran our own mortgage servicer on it. That gave us a real regulated environment to prove our technology could replace the mainframe systems servicers have used for decades. Carrington acquired that servicer and adopted ValonOS as its core platform, allowing us to focus entirely on scaling our SaaS platform.
ValonOS is now on track to power 1 in 6 U.S. mortgages across major mortgage servicers like Newrez, Carrington, and ServiceMac. Every process on the platform is structured and programmable, enabling our AI agents to perform core servicing work, like handling payments, escrow, and homeowner questions, directly within the system's controls.
We recently raised a $150 million Series D at a $2.3 billion valuation by new investor Ribbit Capital, with continued support from existing backer a16z, amongst others.
About the Role
We are seeking a Senior Analytics Engineer to take ownership of our client reporting data models and pipelines. This crucial role involves managing the layer of our data models responsible for transforming raw data into reliable, structured, and performant assets for reporting, analysis, and AI initiatives. This role sits at the intersection of analytics and data engineering, ensuring data is production-grade, auditable, and easily accessible across the organization and our customers.
You will own client reporting, standardize our data modeling practices, manage the orchestration of analytical workflows, and provide hands-on analytical support for high-stakes operational business functions, including reporting and performance management.
Responsibilities
Client Reporting & Infrastructure: Scope and develop new client reports, while also maintaining and enhancing existing reporting pipelines. Collaborate with external clients and our internal client success team to effectively manage and triage inbound requests. Partner with Valon Technologies' data team to improve the underlying infrastructure for client reporting.
Data Modeling & Transformation: Design, build, and maintain the production-grade data models and analytical layers using our existing stack of BigQuery, dbt, and Airflow to ensure reliability and structure at scale.
Data Governance & Quality: Partner with engineering and product teams to define and implement data contracts and observability frameworks to guarantee data quality and auditability for a regulated environment.
Analytical Support: Write complex SQL queries, build dashboards (in tools like Hex or Looker), and conduct ad hoc analysis to empower operational leaders and provide deep root-cause insights into business performance.
Ideal Background & Qualifications
Experience: 7+ years of combined experience in data engineering, analytics engineering, or a highly technical data analytics role, ideally at a technology company or financial institution (Series B–E startup experience is a plus).
Technical Stack: Expertise in SQL (required), strong proficiency in Python, and proven experience with core modern data stack tools like dbt and Airflow.
Communication: Communicate effectively with external clients, clearly synthesizing their requests, establishing realistic timelines, and proactively managing expectations, including pushing back when necessary to ensure successful outcomes.
Architecture & Quality: Deep understanding of data architecture patterns (e.g. medallion architecture) and experience implementing data quality frameworks, observability tools, or data contracts at scale.
Analytical Tools: Experience with data visualization tools (Hex, Looker, or equivalent) and proficiency in Google Sheets/Microsoft Excel.
Mindset: A strong product mindset, focusing on the usability, reliability, and developer experience of the data systems you build.
Problem-Solving: Proven ability to solve complex problems independently and build repeatable processes around novel situations.
Minimum Qualifications
Bachelor’s Degree or equivalent professional experience in Computer Science, Data Analytics, or a similar field.t professional experience in Computer Science, Data Analytics, or a similar field.
Benefits
Compensation: competitive salary and 401(k) plan
Health & well-being: we’ll invest in your physical and mental well-being with comprehensive medical, dental, & vision benefits
Grow together: Company-wide orientation for you to successfully onboard and other learning & development opportunities, including regular review cycles that feature 360-degree feedback
Generous time off: 17 days paid time off, sick days, and 11 company holidays
Baby bonding time!: 12 weeks off for both birthing and non-birthing parents - fully paid so you can focus your energy on your newest addition
Throughout the interview process, please remember that emails will only be from valon.com email addresses. We will never ask for any personally identifiable information during the interview process itself. Please reach out to talent@valon.com if you have any requests to verify the authenticity of an outreach.
Valon is an equal opportunity employer that is committed to diversity and inclusion in the workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, or local laws. Valon makes hiring decisions based solely on qualifications, merit, and business needs at the time.
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- Location & working pattern
New York, United States
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