Senior Data Quality & Observability Engineer (Snowflake)

Posted Yesterday
Be an Early Applicant
Hiring Remotely in USA
Remote
165K-185K Annually
Senior level
Fintech
The Role
Build and own data quality and observability for the data platform: profile data, define quality rules, set metrics/SLAs, monitor and alert, investigate and resolve data issues at source, and partner with data engineering and business stakeholders on standards and reporting.
Summary Generated by Built In
About Allocate

Allocate is transforming private market investing by enabling RIAs and family offices to seamlessly discover, model, and manage their private market exposure. Our platform combines curated fund and co-investment opportunities with institutional-grade infrastructure. Through a single, data-rich digital experience, clients access top-tier opportunities across venture capital, private equity, private credit, and other private asset classes—backed by powerful tracking, analytics, and administration tools.

About the Role

Allocate is looking to add a Senior Data Quality & Observability Engineer to the Data Operations team! There's a lot for us to build, and we need a strong engineer with a broad skillset who can jump right in to help us lay the technical foundation for the company's future.

Essential Responsibilities and Duties
  • Build and own data quality and observability across our data platform.

  • Profile data, define quality rules, and catch issues early.

  • Establish quality metrics, monitoring, and alerting, and track quality SLAs.

  • Investigate and resolve data issues at their source.

  • Partner with data engineering and business stakeholders on quality standards and reporting.

Must Have Experience
  • 5+ years in data engineering, analytics engineering, or data quality, with deep SQL and hands-on Snowflake.

  • Experience with data quality or observability tooling (e.g., dbt tests, Great Expectations, Soda, or Monte Carlo).

  • Hands-on data profiling and experience defining quality rules, metrics, and SLAs.

  • Strong analytical skills and the ability to partner with business stakeholders.

  • Proficiency with Git and version control systems.

  • Hands-on experience with AI-assisted development tools such as Claude Code, OpenAI's Codex, or Cursor, and a demonstrated ability to incorporate new tools as they emerge.

Nice to Haves
  • dbt and modern ELT / orchestration tooling.

  • Data governance, cataloging, or lineage tools.

  • Background in fund, asset-management, or other financial data.

Education
  • Bachelor's degree in a technical or quantitative field, or equivalent practical experience.

Essential Values & Culture
  • Providing our clients with a world-class experience is our number one priority. We obsessively search for ways to improve the experience for our clients and partners—extraordinary response times, proactivity, and a top-tier experience in everything from product strategy to offline communications.

  • Challenge convention: Instead of detailing all the reasons an idea may not work, we question things to determine how a viable idea may be put into motion.

  • Commitment to continuous improvement: We find ways to personally scale each day by pushing ourselves up the learning curve.

  • Meritocracy, not politics: We place the utmost value on results and reward through merit, not political agendas.

  • Civil Discourse is embraced: Open, intellectually curious conversations are required to consistently arrive at the best decisions. Respect is paramount, but the mission is to get the right answer collectively, not to be right.

  • Embrace technological change: We adopt tools and techniques that make us faster, smarter, and better—especially around AI and automation—and drop outdated methods without hesitation.

Additional Details
  • Location: Fully Remote (all I-9 eligible candidates will be considered).

  • Employment: Full-time. Seniority: Senior professional.

  • Salary: The expected base salary range for this role is $165,000 to $185,000. Actual compensation will be determined based on the candidate's primary work location and other job-related factors including skills, experience, qualifications, interview performance, internal equity, and market data. Candidates located in higher cost-of-living markets, including the San Francisco Bay Area, may be considered within the higher end of the range. This range reflects base salary only and does not include bonus, equity, or benefits; total compensation may also include a discretionary performance-based bonus.

  • Benefits: Medical, dental, and vision; 401(k); and responsible vacation time (PTO).

  • Travel required for team and department offsites. An in-person interview may be required during the process. A broadband internet connection is required. Compliance with Allocate's Code of Ethics is a given for this role.

Skills Required

  • 5+ years in data engineering, analytics engineering, or data quality
  • Deep SQL skills
  • Hands-on Snowflake experience
  • Experience with data quality or observability tooling (dbt tests, Great Expectations, Soda, Monte Carlo)
  • Hands-on data profiling and defining quality rules, metrics, and SLAs
  • Strong analytical skills and ability to partner with business stakeholders
  • Proficiency with Git and version control systems
  • Hands-on experience with AI-assisted development tools (e.g., Claude Code, OpenAI Codex, Cursor)
  • Bachelor's degree in a technical or quantitative field, or equivalent practical experience
  • dbt and modern ELT / orchestration tooling
  • Experience with data governance, cataloging, or lineage tools
  • Background in fund, asset-management, or other financial data
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The Company
HQ: Palo Alto, CA

What We Do

Alternative investments have become a growing staple in investor portfolios as investors continue to seek better portfolio diversification and higher returns. However investing in and alongside the most promising venture funds is primarily limited to institutional investors and industry insiders. We are here to change that.

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