Senior Analytics Engineer

ZBD; United States; Remote; USD 120,000 - 160,000; Full time

Job summary

ZBD is hiring a Senior Analytics Engineer to design and build the modeling layer that the business relies on. You will stand up dbt on a new warehouse, transform data into trustworthy models for finance, compliance, and product, and shape scalable foundations with patterns for the team.

You will report to the VP, Data and work remotely with the Engineering department to enable advanced analytics and reporting across the organization.

Qualifications

• 7+ years of combined experience across analytics engineering, data engineering, or analytics roles with substantial modeling ownership.
• Strong analytical SQL skills - complex joins, window functions, performance-aware queries.
• Data modeling / dimensional modeling fluency - design schemas from fuzzy requirements.

Responsibilities

• Own the transformation layer, including dimensional models, tests, and documentation, as we stand up dbt on a new warehouse
• Turn business questions into durable models. Not all work arrives fully specified, so you’ll turn ambiguity into structure and set patterns the team builds against.
• Partner with finance, compliance, and product to define requirements, data definitions, and what “correct” means in our business context
• Monitor what you build, catching and resolving or escalating issues before our stakeholders notice
• Go a layer down into data ingestion, orchestration, or warehouse configuration when warranted, or go a layer up into analysis and decision support when needed

Skills

SQL

Data modeling

Analytics

CI/CD practices

Tools

dbt

Airflow

Dagster

Prefect

Metabase

Hex

Looker

Tableau

Git

Job description

Description

We’re hiring a Senior Analytics Engineer to build the modeling layer that the rest of the business runs on. This role will be responsible for the transformation layer as we stand up dbt on a new warehouse. You will design and build trustworthy models that finance, compliance, and our product depend on. You will help architect a scalable foundation and set patterns for the team as we drive advanced analytics and reporting across the organization. You will report to the VP, Data.

Department: Engineering

Location: Remote

Description

We’re hiring a Senior Analytics Engineer to build the modeling layer that the rest of the business runs on. This role will be responsible for the transformation layer as we stand up dbt on a new warehouse. You will design and build trustworthy models that finance, compliance, and our product depend on. You will help architect a scalable foundation and set patterns for the team as we drive advanced analytics and reporting across the organization. You will report to the VP, Data.

What you'll do

• Own the transformation layer, including dimensional models, tests, and documentation, as we stand up dbt on a new warehouse
• Turn business questions into durable models. Not all work arrives fully specified, so you’ll turn ambiguity into structure and set patterns the team builds against.
• Partner with finance, compliance, and product to define requirements, data definitions, and what “correct” means in our business context
• Monitor what you build, catching and resolving or escalating issues before our stakeholders notice
• Go a layer down into data ingestion, orchestration, or warehouse configuration when warranted, or go a layer up into analysis and decision support when needed

What we're looking for

• 7+ years of combined experience across analytics engineering, data engineering, or analytics roles with substantial modeling ownership
• Strong analytical SQL skills - complex joins, window functions, performance-aware queries
• Data modeling / dimensional modeling fluency - you can design schemas from fuzzy requirements, not just query what exists
• Transformation framework experience - dbt preferred, with Dataform, SQLMesh, or equivalent acceptable
• Cloud data warehouse experience - Redshift, Snowflake, BigQuery, Databricks, or equivalent
• Orchestration engine familiarity - Airflow, Dagster, Prefect, or equivalent
• BI / Visualization layer familiarity - Metabase, Hex, Looker, Tableau, or similar
• Engineering hygiene - Git, CI/CD, testing, documentation
• Stakeholder range - you can sit with a finance or compliance lead, ask questions to get to requirements, and leave with a definition you can build against

Bonus experience we’re also interested in:

• Platform-level experience - working with tools like Terraform / infra-as-code, DMS / CDC, data lake patterns, and data observability
• Experience with financial, payments, or otherwise regulated data - it shortens the learning ramp.