# Senior Analytics Engineer

**Company:** [Luxury Presence](https://hotfix.jobs/companies/luxury-presence)
**Location:** Remote
**Role:** Data Engineering
**Salary:** $150k – $190k/yr
**Experience:** 5+ years
**Skills:** SQL, dbt, Python, Snowflake, apache airflow, Salesforce, ELT, BigQuery, amazon redshift, CI/CD, Git, automated testing, posthog, Mixpanel, snowflake cortex
**Posted:** 2026-08-10

> Builds and scales the analytical data foundation across business and product teams, owning dbt models, Snowflake, Python/Airflow pipelines, reconciliation, data quality, and semantic layers for AI tools. Requires 5+ years of analytics or data engineering experience with strong SQL, dbt, Python, and SaaS data expertise.

## Job Description

## Responsibilities

### Build & Own the Data Foundation
- Own and evolve the **dbt** project, ensuring models are performant, well-tested, and documented.
- Design and maintain the **Snowflake** data warehouse and ingestion processes.
- Create core entities and datasets using modern data-modeling practices for complex business processes and logic.
- Build and maintain custom **Python/Airflow** pipelines to ingest third-party APIs into Snowflake.
- Design and operate cross-system reconciliation models to compare source-system data, surface discrepancies, and protect revenue.

### Drive Data Quality & Automation
- Implement testing and observability for analytics pipelines.
- Enforce CI/CD practices including automation, linting, testing, code review, and approvals.
- Standardize metric definitions across tools.
- Investigate and document data incidents from root-cause analysis through remediation tracking and stakeholder communication.

### Cross-Functional Collaboration
- Act as a data liaison between Engineering, GTM, and Finance to ensure consistent metric definitions and proper system instrumentation.
- Enable stakeholder self-service access to trusted insights.
- Promote data literacy and coach stakeholders on querying, dashboarding, and metric interpretation.

### Build AI-Ready Data Infrastructure
- Design and maintain **Snowflake Cortex semantic views** as governed data interfaces for AI agents and LLM-powered tools.
- Partner with AI and product teams to scope, build, and validate semantic-layer definitions for internal AI assistants.
- Build measurement frameworks for AI-powered initiatives, including experiment design and attribution modeling.

## Requirements
- 5+ years of experience as an analytics engineer, data engineer, or similar role in a SaaS environment.
- Deep expertise in SQL, dbt, and modern data modeling.
- Proficiency in Python for pipeline development, API integrations, and automation.
- Experience modeling Salesforce data, including opportunities, contracts, subscriptions, cases, and field history.
- Experience building custom ELT pipelines that ingest third-party APIs into a cloud data warehouse.
- Experience designing cross-system reconciliation models involving joins, deduplication, and source-data comparisons.
- Experience with event-based and product-usage data such as PostHog or Mixpanel.
- Experience connecting marketing data, including paid ads, campaigns, and attribution, to product analytics.
- Experience designing and maintaining governed semantic layers, such as dbt Semantic Layer or Snowflake Cortex.
- Familiarity with large-scale data systems including Snowflake, BigQuery, or Redshift.
- Strong familiarity with CI/CD, Git-based workflows, and automated testing.
- Experience collaborating with engineers, analysts, and product managers.
- Demonstrated success using analytics to drive decisions in technical or product-focused environments.
- Comfort taking ownership of ambiguous problems and designing end-to-end solutions.

## Nice-to-Haves
- Experience building and maintaining Airflow DAGs and orchestrating multi-source API ingestion pipelines.
- Strong foundation in statistics and experiment design, including A/B testing, significance testing, and incremental-impact measurement.
- Experience with predictive-modeling fundamentals, including classification, feature selection, and model evaluation.
- Familiarity with financial SaaS metrics and billing operations, including ARR, MRR, NRR, subscription reconciliation, and revenue recognition.
- Experience with people analytics, including headcount, attrition, and compensation benchmarking.

## Compensation
- Annual salary range: $150,000–$190,000.

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