Senior Analytics Platform Engineer

Salesforce Staffing, LLC; United States; Remote; USD 160,000 - 190,000; Full time

Job summary

Salesforce Staffing, LLC is hiring a Senior Analytics Engineer to build a data and analytics foundation from the ground up in a remote United States role. You’ll own the technical stack, stand up a warehouse and semantic layer, and implement trusted metrics for reporting and self-service analytics.

You will shape the BI strategy, prioritize source data, and deliver scalable data products across Sales, Finance, Customer Success, Product, and more, with an eye toward AI-enabled insights.

Qualifications

• 6+ years in analytics engineering, data engineering, BI engineering, or similar role.
• Strong SQL and production data models; experience with ELT/ETL, ingestion, and data lineage.
• Experience with a modern cloud warehouse (Snowflake preferred) and a transformation framework (dbt, SQLMesh, etc.).
• Python or similar scripting for automation and data ingestion.
• Experience with semantic modeling and BI/semantic-layer tools (Omni, Looker, LookML, dbt Semantic Layer).

Responsibilities

• Define and implement the modern analytics stack: warehouse, ingestion/ELT, transformation, governance, BI, and semantic-layer tooling.
• Lead the centralized cloud warehouse buildout and reliable pipelines across core systems.
• Establish a governed semantic layer with trusted metrics and business-friendly models for reporting.
• Shape and implement the BI strategy using Omni or a similar platform.
• Build durable models for pipeline, bookings, ARR, renewals, and other SaaS metrics.
• Partner with business leaders to turn questions into trusted data products and enable AI-ready analytics.

Skills

SQL

Data modeling

ELT/ETL

dbt

Python

Semantic modeling

Looker

Snowflake

Tools

Snowflake

dbt

Looker

Omni

SQLMesh

Job description

Salesforce Staffing, LLC is hiring a Senior Analytics Engineer to build a data and analytics foundation from the ground up in a remote United States role. You’ll own the technical stack, stand up a warehouse and semantic layer, and implement trusted metrics for reporting and self-service analytics.

You will shape the BI strategy, prioritize source data, and deliver scalable data products across Sales, Finance, Customer Success, Product, and more, with an eye toward AI-enabled insights.