Ibotta

2 months ago

Data Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 21 hours agoStatus: Live

Job Summary

Data Engineer within the Data Platform Organization to build data contracts, metadata standards, AI readiness scoring, governance and semantic layers, and AI-assisted development for an AI-ready data estate. You’ll collaborate across teams to ensure data quality, privacy guardrails, and trusted AI outputs, with growth into LLM applications.

Location: Denver

Workplace: Hybrid

Employment Type: Full time

Job Function: Software Engineering

Key Responsibilities

•Data Contract and Metadata Standards: Implement and maintain data contract specifications that codify table ownership, schema expectations, and quality thresholds; enforce standards through automated validation in the deployment pipeline; collaborate with data owners to improve metadata coverage across the team’s data estate.
•AI Readiness Scoring: Contribute to an automated scoring pipeline that evaluates data assets on their readiness for AI and analytical use; build and maintain the jobs that collect quality signals and surface scores to data teams.
•AI Governance and Compliance: Support the discovery and classification of sensitive data across the data estate; maintain tagging and lineage automation frameworks; help translate data access and privacy policies into practical guardrails in partnership with the platform team; monitor AI usage across the company, defining new avenues for AI assistance.
•AI Trust and Reliability: Build the systems that make people actually trust what the AI tells them about our data, such as query accuracy checks, guardrails that keep AI tools on certified data, and clear attribution so users can see where an answer came from; monitor for problems before they erode confidence.
•Semantic Layer Contributions: Build and maintain the semantic framework that make data assets more legible to both people and AI systems, adding descriptions, context, and query guidance to improve NLQ accuracy; collaborate with analysts and domain experts to capture business definitions.

Pay and Benefits

Equity and Bonus:Equity

Perks:Health Insurance401kEquity

Key Requirements

•3+ years of software engineering experience with a focus on data engineering, analytics engineering, or backend development.
•Proficiency in Python and SQL, knowledge of Databricks, and familiarity with medallion architecture (bronze/silver/gold) or similar layered data design patterns.
•Experience implementing semantic layers to ensure AI agents utilize governed, consistent metric definitions rather than querying raw tables directly.
•Understanding of data governance concepts (metadata standards, data ownership, schema enforcement, access control) and keeping data assets clean and well-documented.
•Experience with schema validation, data freshness monitoring, data observability tooling, or similar quality practices.

Experience:3+ yearsData engineeringAIAnalytics engineeringBackend development

Education:Bachelor's

Skills:PythonSQLDatabricksLLMsNQLsCursorClaudeCopilotGitCI/CDData governanceData lineageMetadata managementData qualitySchema validationObservability

Tech Stack:PythonSQLDatabricksLLM toolingMetadata managementData governanceData lineageCI/CD

Eligibility

Work Authorization:Authorization required. Sponsorship not provided.

Company Brief

Ibotta

Ibotta is a mobile cashback and rewards platform that enables consumers to earn rebates and discounts on grocery, retail, and online purchases while providing brands and retailers with promotional and shopper insights.

Industry: E-commerce

Company Size: Large (251 to 1,000 employees)

Growth: Established Company

Funding: Series D

Headquarters: Denver, United States

Founded: 2012

Website LinkedIn

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Ibotta

2 months ago

Data Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 21 hours agoStatus: Live

Job Summary

Location: Denver

Workplace: Hybrid

Employment Type: Full time

Job Function: Software Engineering

Key Responsibilities

•Data Contract and Metadata Standards: Implement and maintain data contract specifications that codify table ownership, schema expectations, and quality thresholds; enforce standards through automated validation in the deployment pipeline; collaborate with data owners to improve metadata coverage across the team’s data estate.
•AI Readiness Scoring: Contribute to an automated scoring pipeline that evaluates data assets on their readiness for AI and analytical use; build and maintain the jobs that collect quality signals and surface scores to data teams.
•AI Governance and Compliance: Support the discovery and classification of sensitive data across the data estate; maintain tagging and lineage automation frameworks; help translate data access and privacy policies into practical guardrails in partnership with the platform team; monitor AI usage across the company, defining new avenues for AI assistance.
•AI Trust and Reliability: Build the systems that make people actually trust what the AI tells them about our data, such as query accuracy checks, guardrails that keep AI tools on certified data, and clear attribution so users can see where an answer came from; monitor for problems before they erode confidence.
•Semantic Layer Contributions: Build and maintain the semantic framework that make data assets more legible to both people and AI systems, adding descriptions, context, and query guidance to improve NLQ accuracy; collaborate with analysts and domain experts to capture business definitions.

Pay and Benefits

Equity and Bonus:Equity

Perks:Health Insurance401kEquity

Key Requirements

•3+ years of software engineering experience with a focus on data engineering, analytics engineering, or backend development.
•Proficiency in Python and SQL, knowledge of Databricks, and familiarity with medallion architecture (bronze/silver/gold) or similar layered data design patterns.
•Experience implementing semantic layers to ensure AI agents utilize governed, consistent metric definitions rather than querying raw tables directly.
•Understanding of data governance concepts (metadata standards, data ownership, schema enforcement, access control) and keeping data assets clean and well-documented.
•Experience with schema validation, data freshness monitoring, data observability tooling, or similar quality practices.

Experience:3+ yearsData engineeringAIAnalytics engineeringBackend development

Education:Bachelor's

Skills:PythonSQLDatabricksLLMsNQLsCursorClaudeCopilotGitCI/CDData governanceData lineageMetadata managementData qualitySchema validationObservability

Tech Stack:PythonSQLDatabricksLLM toolingMetadata managementData governanceData lineageCI/CD

Eligibility

Work Authorization:Authorization required. Sponsorship not provided.

Company Brief

Ibotta

Industry: E-commerce

Company Size: Large (251 to 1,000 employees)

Growth: Established Company

Funding: Series D

Headquarters: Denver, United States

Founded: 2012

Website LinkedIn