Senior Analytics Engineer — AI-Ready Data Platform

Socket.dev; United States; Remote; USD 140,000 - 210,000; Full time

Job summary

Luxury Presence is seeking a Senior Analytics Engineer to build and scale the analytical foundation powering decision-making across GTM, Product, Finance, People, and Operations. You will transform raw product, marketing, financial, and operational data into clean, well-modeled datasets and support dashboards, experimentation, billing operations, and AI-enabled insights.

You’ll partner with Product, Marketing, RevOps, Finance, People Ops, and Engineering to ensure a robust, scalable analytics

Qualifications

• 5+ years of analytics engineering or data engineering experience in SaaS.
• Expertise in SQL, dbt, and modern data modeling practices.
• Proficiency in Python for pipelines, API integrations, and automation.
• Experience modeling Salesforce data and building ELT pipelines.

Responsibilities

• Build and evolve a scalable analytics foundation for GTM, Product, Finance, People, and Ops.
• Transform raw data into clean, well-modeled datasets powering dashboards and analyses.
• Design and operate dbt projects, Snowflake warehouse, and ingestion processes.
• Develop Python/Airflow pipelines to ingest data from third-party APIs into Snowflake.
• Create cross-system reconciliation models to surface discrepancies and protect revenue.
• Establish testing, observability, and CI/CD for analytics pipelines.
• Collaborate with engineers, analysts, and product managers to enable self-serve insights.

Skills

SQL

dbt

Python

Salesforce data modeling

ELT pipelines

Data reconciliation

Event-based data

Semantic layer

Snowflake

BigQuery/Redshift

CI/CD

Git workflows

Tools

dbt

Snowflake

Airflow

Posthog

Mixpanel

Salesforce

Job description

Luxury Presence is seeking a Senior Analytics Engineer to build and scale the analytical foundation powering decision-making across GTM, Product, Finance, People, and Operations. You will transform raw product, marketing, financial, and operational data into clean, well-modeled datasets and support dashboards, experimentation, billing operations, and AI-enabled insights.

You’ll partner with Product, Marketing, RevOps, Finance, People Ops, and Engineering to ensure a robust, scalable analytics