Gem

Software Engineer - Data Platform

Gem$90K — $130K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of experience in data pipeline or aggregation layer development
  • Strong understanding of relational and dimensional modeling
  • Ability to transform insights into actionable business changes
  • Daily use of AI coding agents for efficiency
  • Proficient in multiple programming languages and tools
  • End-to-end ownership of complex, ambiguous problems
  • Experience in building reliable data platforms and maintaining their integrity

Responsibilities

  • Develop and maintain data ingestion and processing pipelines
  • Design and implement relational and dimensional data models
  • Manage data aggregation, rollup, and quality assurance processes
  • Ensure multi-tenant data isolation and secure access controls
  • Create APIs and services for data consumption across various platforms
  • Design self-service reporting and ad-hoc query interfaces
  • Ground and evaluate LLM systems against trusted data

Benefits

  • Medical, Dental, and Vision insurance starts on day one
  • Unlimited PTO with a mandate for minimum annual leave
  • 401K plan with company matching
  • Flexible remote work options
  • Generous parental leave policy
  • Recognition as one of America's Fastest Growing Private Companies
  • Active employee-led Culture Committee
  • Ongoing professional development and training opportunities
Full Job Description
The Opportunity

Vantaca IQ is the intelligence layer at the core of Vantaca's platform, and this team builds it. You take messy, multi-tenant operational data, organize it, and turn it into the insights and signals the platform acts on - surfaced where decisions get made and served to HOAi agents that act on it. You own the stack that makes that possible: ingestion and pipelines; the schemas and aggregation beneath every report; the reporting and ad-hoc query surfaces; the derived-intelligence layer; and the semantic and ontological model on top. You make community management legible to LLMs.

IQ is data-as-a-service, one governed source feeding humans and agents where they are - proactive, personalized, channel-agnostic. The hard problems sit here: serving cross-tenant data without leaking a byte, semantic governance that keeps one number from forking into five, eval harnesses that prove a grounded LLM is right, and pipelines trustworthy enough to bill against and report to boards.

What the Team Owns

  • Ingestion & pipelines: batch and change-data-capture out of the operational system of record; transformations, scheduling, backfills, and idempotent reprocessing.
  • Data models & metric layer: relational and dimensional schemas, and define-once metrics with the thoughtful governance.
  • Aggregation, rollups & derived metrics: materializations, incremental rollups, and partitioning/indexing for fast, cheap queries - plus the score and benchmark jobs, with the data-quality checks, lineage, and tests that keep them correct.
  • Multi-tenant isolation: tenant-scoped access and row/column controls on every surface, including cross-tenant aggregates that expose no individual tenant's data.
  • Access & serving layer: how every consumer reads the platform's intelligence - query and metrics APIs, an MCP server for agents and external tools, embeddable feeds, and push to Teams and Slack - one governed contract whether the caller is a person, an app, or an agent.
  • Reporting & ad-hoc surfaces: report definitions, board-packet generation, and self-serve query interfaces.
  • LLM grounding & evals: the retrieval/semantic interface an LLM queries against, and the eval harnesses that measure and gate accuracy.
  • Signal & action contracts: insight-detection jobs and the typed, audited output contracts HOAi agents consume to act.


What We're Looking For

At every level:

  • Data fundamentals: you've built pipelines or aggregation layers over messy operational data and understand how analytical engines execute your queries.
  • Modeling instinct: relational and dimensional modeling, and the conviction that every metric you publish is an interface someone, or some agent, depends on.
  • Product sense for data: you care that an insight changes how our userd do business.
  • AI-native by default: Active daily use of AI coding agents (Claude Code, Cursor, or similar); this is a baseline, not a differentiator.
  • Polyglot and pragmatic: You reach for the right tool to solve each problem, while thoughtfully evolving the ecosystem.
  • Curiosity and ownership: you run at ambiguous problems and take systems end-to-end (build 14 ship 14 operate).


At senior levels, additionally:

  • Source-of-truth scar tissue: you've built a data platform other teams trusted and kept it trustworthy as it grew.
  • Semantic governance: you've defined semantic-layer or metric-governance architecture and lived with the consequences.
  • Grounded-LLM receipts: you've shipped or evaluated an LLM system grounded in governed data and can explain what you measured.
  • Raising the bar: testing strategy, documentation, and mentoring.


How leveling works: Leveling is set during the interview process by demonstrated scope and impact - growing fast and thinking clearly often beats more years and logos.

Nice to Have

  • Semantic-layer or metrics-store experience (e.g., MetricFlow, LookML, Cube, dbt, or similar).
  • Modern data stack exposure (e.g., warehouses, lakehouses, event streaming, and orchestration tools).
  • Multi-tenant analytics or cross-customer benchmarking - serving derived intelligence without leaking anyone's data.
  • Exposure to property management, HOA, or real estate tech - helpful but not required.


Core Values

  • Always Growing: Likes change and enjoys finding new ways to improve their knowledge and the platform. Always ready to learn quickly about emerging AI technologies and infrastructure patterns, helping themselves and the team grow.
  • Win as a Team: Builds trust and works together by making sure everyone communicates well. Actively involved in daily platform work, working closely with engineering teams, listening to their infrastructure needs, and celebrating technical successes together.
  • Accountability Starts with Me: Notices platform problems and takes personal action to solve them. Takes ownership of platform performance, reliability, and the success of internal customers building on the platform.
  • Unwavering Commitment to Customer Experience: Regularly talks to internal customers (product teams, engineers), taking personal responsibility to understand what they need from the platform, address infrastructure concerns, and make their development experience better with improved platform capabilities.
  • Innovate Boldly: We challenge the status quo and push technical boundaries to create meaningful change. We act with urgency and purpose, knowing that platform innovation drives our AI-native product success.


Why You Should Join Our Team

  • AI-First Product Culture - Build the intelligent infrastructure that powers AI innovation at scale
  • Our eNPS is +68! (Google it, that is great)
  • Benefits: Medical, Dental, and Vision kick in day one
  • Unlimited PTO (with a requirement for employees to take a minimum of one continuous week per year)
  • 401K with Company Match
  • Remote Flexible - come to the office when needed
  • Great parental leave benefits
  • Named on Inc 5000 list of America's Fastest Growing Private Companies
  • Named on Inc 5000 Vet 100 Private Companies list multiple years in a row
  • Winner of Coastal Entrepreneur Award, Technology Category
  • Active employee-led Culture Committee
  • Ongoing industry and professional development trainings available to all employees
  • Multiple leaders on the executive committee recognized as 40 under 40 recipients for contributions to business and community
  • We're playing offense to win! Our product market fit and our world-class employees make us the leader in our space. We're building something cool and people like it here

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