Senior Analytics Engineer

Collaborative Solutions•Jersey City, NJ

23h•Hybrid

About The Position

Collectors is the leading creator of innovative technology that provides value-added services for collectors worldwide. We grade, authenticate, vault, and sell millions of record-setting collectibles, all while modernizing and digitalizing the process to further our mission of helping collectors pursue their passions. We’re always on the lookout for talented people to join our growing team. Our services span collectible trading cards, autographs, comic books, coins, video games, event tickets, and memorabilia. Our subsidiaries include PSA, PCGS, Beckett, SGC, and Card Ladder. Since our founding in 1986, we have graded and authenticated millions of items. We employ more than 3000 people across our headquarters in Santa Ana, California and offices in New Jersey, Texas, Florida, Japan, Shanghai, Hong Kong, Canada, Mexico, Germany, and France. As part of our interview process, we request that candidates have their cameras on during video interviews. This helps foster meaningful conversation and allows us to create an experience that closely resembles our standard working environment. Certain interview steps may take place by phone. For remote roles, and at our discretion, candidates may be asked to participate in an on-site interview as part of the final stages of the process. We understand there may be occasional circumstances requiring accommodation and are happy to discuss them as needed. Your recruiter will be able to clarify expectations and answer any questions you have. We're transforming the collecting experience with technology that brings authentication, grading, and trading into the modern era. Our products are equalizing the playing field by providing tools that make complex research analytics — including pricing, scarcity reports, and historic sales data — accessible to every collector, old or new. Our engineering mission is to democratize technology while promoting innovation, collaboration, and continuous learning throughout the organization. We're looking for a Senior Analytics Engineer to help build the trusted analytical layer of our data platform. You'll own data models and metrics end-to-end — from raw data in our warehouse through dbt transformations to the semantic layer in Lightdash — turning our data into consistent, well-governed answers that stakeholders and AI agents alike can rely on. You'll report to the Staff Manager, Data Engineering & Analytics. Remote or hybrid candidates will also be considered. We believe that there is significant value in in-person collaboration. If you live within a 1 hour commuting distance to one of our offices, you will be required to be onsite most of the time. This will be discussed further as part of the recruiting process.

Requirements

An experienced analytics engineer with 5+ years in analytics engineering, data engineering, or a similar role, with a proven ability to model data for reporting and analytics needs.
Highly experienced with dbt, applying the best practices of software engineering — modularity, testing, code review, documentation — to data transformation.
An expert in the modern data stack, with hands-on experience across cloud data warehousing (BigQuery or equivalent), data transformation, and workflow orchestration.
Experienced with a modern BI / semantic layer such as Lightdash, Looker, or similar — and opinionated on where the metrics layer is heading and why it matters more, not less, in an agentic world.
Fluent in AI-assisted development. You have real experience developing with Claude Code or a similar coding agent, or you're eager to make AI-driven workflows a core part of how you build.
Analytically minded. You have experience with or a strong interest in the analytical side of data — collecting requirements, defining and implementing metrics, and developing dashboards that tell a clear story.
A strong cross-functional partner. You build trust with stakeholders easily, translate business questions into well-modeled data, and communicate clearly with both technical and non-technical audiences.
Technically fluent. You're proficient in SQL and Python, with a strong working knowledge of software engineering workflow tools such as version control, CI/CD, and testing.

Responsibilities

Design and build our data models and transformations, applying software engineering best practices in dbt on top of our Google BigQuery warehouse to produce datasets that are accurate, performant, and easy to reason about.
Own the semantic layer in Lightdash, defining metrics, dimensions, and governed datasets so the business gets one consistent, trusted answer to every question — no matter who (or what) is asking.
Act as a leader for our data modeling standards, shaping conventions, review practices, and documentation that keep the transformation layer maintainable as it grows.
Develop end-to-end with AI coding agents. Our teams build with Claude Code and similar tools, and you'll use AI-assisted workflows to move faster while upholding quality through testing and review.
Enable AI-driven analytics, treating the semantic and governance layers as the foundation that agents and MCP connections build on to deliver trustworthy, self-serve answers from data.
Advance metric governance and definitional consistency, contributing to the auditability and reporting rigor expected of a company operating at scale and under growing scrutiny.
Partner with cross-functional stakeholders to gather requirements, identify high-value reporting and dashboarding use cases, and ship the models and metrics that drive decisions.
Train and enable users on self-serve analytics capabilities and best practices, growing the number of people across the business who can confidently answer their own questions with data.