Lead Analytics 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

Remote – United States | Full-Time | Revenue Operations

Base salary: $160,000–$190,000 + 10% target bonus

Note - You must be authorized to work full-time in the United States without current or future employer sponsorship.

My client is hiring a Senior Analytics Engineer to build the company’s data and analytics foundation from the ground up.

Today, critical data lives across Sales, Finance, Customer Success, Product, and other systems. There is not yet a centralized warehouse, shared metric definitions, or a reliable semantic layer. This person will help change that.

You will own the technical foundation for trusted reporting and decision-making: helping shape the stack, standing up the warehouse and transformation layer, bringing in priority source data, establishing governed metrics and semantic models, and creating a scalable BI strategy.

Snowflake is the likely warehouse direction, and Omni is the likely BI platform, but neither is fully locked. We want someone who has done this before and can bring strong, practical judgment on architecture, tooling, and sequencing—not someone looking to inherit a fully defined environment.

This is a high-ownership, greenfield build. You will report directly to the Revenue Strategy and Analytics leader, work in a hands-off environment, and have the autonomy to take a project from ambiguity to a well-executed outcome.

What You’ll Do

• Help define and implement the modern analytics stack: warehouse, ingestion/ELT, transformation, testing, documentation, governance, BI, and semantic-layer tooling.
• Lead the buildout of a centralized cloud warehouse—likely Snowflake—and create reliable pipelines and production-grade models across Salesforce, Finance, Customer Success, Product, and other core systems.
• Establish a governed semantic layer with trusted metric definitions, reusable dimensions, appropriate access controls, and business-friendly models for reporting and self-service analytics.
• Shape and implement the BI strategy, likely using Omni or a comparable modern platform.
• Build durable models for pipeline, bookings, ARR, renewals, customer adoption, account health, and the other metrics that run a SaaS business.
• Create the foundation for product analytics, including product-usage data, event tracking, and event-level analysis.
• Partner directly with business leaders to turn ambiguous questions into trusted data products, while building an AI-ready foundation for future natural-language and AI-assisted reporting.

What We’re Looking For

• 6+ years in analytics engineering, data engineering, BI engineering, or a similar role, with experience building or materially modernizing a warehouse, analytics platform, BI strategy, or governed reporting environment.
• Strong SQL and hands-on experience building production data models, plus practical experience with ELT/ETL, ingestion, orchestration, testing, observability, documentation, and data lineage.
• Experience with a modern cloud warehouse—Snowflake strongly preferred—and a transformation framework such as dbt, SQLMesh, or a comparable production-grade workflow.
• Python or similar scripting experience for automation, ingestion, validation, or API integrations.
• Strong experience with semantic modeling and a modern BI or semantic-layer tool. Omni, Looker, LookML, Cube, AtScale, or dbt Semantic Layer experience is especially relevant.
• SaaS experience is strongly preferred, especially working with Salesforce and supporting revenue operations, customer success, product usage, adoption, retention, renewals, or ARR reporting.
• High ownership, sound judgment, and strong stakeholder skills. You can clarify ambiguity, make thoughtful technical recommendations, communicate directly, and drive work to completion without close day-to-day management.

A Strong Plus

• You have selected or implemented a modern data stack in a greenfield or high-growth environment.
• You have direct Snowflake and/or Omni Analytics experience.
• You have worked with product-event data, product instrumentation, feature adoption, or usage analytics.
• You have integrated data from Salesforce, customer-success tools, billing platforms, product-event tools, support systems, marketing automation, or finance systems.
• You have built semantic layers or governed data products that support self-service BI, natural-language querying, or AI-assisted analytics.

Who This Is Not For

This is not a dashboard-maintenance or Tableau-heavy role. It is not a pure data-science or machine-learning role, either.

It is probably not the right fit if you want a fully established stack, narrowly defined tickets, clean source data, or frequent day-to-day direction. We are looking for a senior builder who is comfortable with ambiguity, can bring order to fragmented operational data, and enjoys owning a foundational platform.

You must be authorized to work full-time in the United States without current or future employer sponsorship.

Why This Role

You will have the opportunity to build a durable analytics foundation with high visibility across the business. The work has a multi-year runway: centralizing source data, standardizing key metrics, building reporting and semantic models, supporting SaaS product analytics, and establishing the trusted data layer needed for future AI-enabled analytics.

The role is an individual-contributor position today, with the opportunity to help shape a growing analytics function over time.