Pay
$122K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 321 postings in the last year. Stated ranges, not salaries paid.
New York · New York, United States
Actively hiring, first seen by us 10 days agoLocation type: On-siteFrom the employer’s posting
Employment type: Full-timeFrom the employer’s posting
Department: DataFrom the employer’s posting
Do you now, or will you at any point in the future, require sponsorship?From the employer’s application form
We 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
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.
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.
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
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
Actively hiringFirst seen by us 10 days ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
$122K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 321 postings in the last year. Stated ranges, not salaries paid.
Day 10
Similar jobs usually come down between day 6 and day 47.
From 1,405 similar postings that came down. Coming down is not always a hire.
2 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordAdd your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- 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.
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We file this job under Analytics Engineer, by the work the posting describes.
Analytics engineers turn raw warehouse data into clean, tested and documented tables that analysts and dashboards can rely on, often with dbt.
Expect strong SQL, data modeling, Git, and a warehouse such as Snowflake, BigQuery or Redshift.
A data engineer gets data into the warehouse; an analytics engineer shapes it once it is there and works closer to the analysts who use it.
The government has no code for analytics engineers, so these figures are for the closest group, database architects, the same group we use for data engineers.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
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.
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.
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.
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.
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.
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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New York, United States
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