Staff Data Engineer

NABIS

Staff Data Engineer building and maintaining data pipelines for Nabis, the leading cannabis wholesale platform. Focused on performance, reliability, and accessibility of data for analytics.

Posted 7/2/2026full-timeRemote • California, Colorado, Florida, Idaho, Illinois, Iowa, Kansas, Maine, Maryland, Massachusetts, Missouri, Montana, Nevada, New Jersey, New York, Tennessee, Texas, Utah, Virginia, Washington • 🇺🇸 United StatesLead💰 $145,000 - $170,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in building and optimizing data ingestion pipelines, utilizing dbt for data transformation, and ensuring data quality and performance in cloud data systems. Proficient in Python and familiar with CI/CD practices to support robust data applications and analytics.

Highest-signal resume keywords

Data Ingestion Pipeline DevelopmentAdvanced Dbt ProficiencyCloud Data Systems ManagementPython ProgrammingCI/CD Pipeline Experience

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

SQLJinjaAPIsChange Data Capture (CDC)Data Quality ChecksData Lake/Warehouse OptimizationData Application DevelopmentMonitoring and Alerting FrameworksVersion Control (Git)Cloud Data Systems

Tools & Technologies

DbtSnowflakeBigQueryDatabricks

Industry Keywords

Data EngineeringData AnalyticsData FreshnessPlatform Reliability

Tech Stack

Tools & technologies

BigQueryCloudPythonSQL

About the role

Key responsibilities & impact

Own the building, maintenance, and optimization of pipelines to ingest data from both operational databases and third-party tools into a data lake/warehouse.
Architect highly efficient ingestion patterns that handle evolving data schemas and high-volume, multi-source data streams seamlessly.
Optimize pipeline performance to ensure maximum uptime, high throughput, and cost-effective compute usage.
Use dbt to transform raw data within the data warehouse into structured, production-ready schemas.
Write templated SQL and Jinja code to enforce macro-driven, modular, and DRY (Don't Repeat Yourself) development practices.
Perform rigorous data quality checks by implementing native dbt tests.
Set up monitoring and alerting frameworks around both ingestion routines and dbt builds.
Track pipeline health metrics to measure and report on overall data freshness and platform reliability.
Build data applications that interact with the data warehouse to empower decentralized self-service analytics.
Build internal tooling and libraries to facilitate analytics and ML work.

Requirements

What you’ll need

Proven production experience building, scaling, and maintaining robust ingestion pipelines using APIs, CDC (Change Data Capture), and orchestrators.
Advanced proficiency in dbt, including production deployments, package management, and writing custom Jinja macros.
Strong hands-on experience manipulating and managing data within cloud data systems (e.g. Snowflake, BigQuery, Databricks).
Strong proficiency in Python or similar back-end languages to build operational applications and custom pipeline tooling.
Experience setting up alerting infrastructure and working with version control (Git) and CI/CD pipelines.

Benefits

Comp & perks

Unlimited PTO and paid holidays
Medical/Dental/Vision offered to all full-time employees
401(k) plan with a match.