WHAT YOU’LL DO:

BRUNT is at a pivotal inflection point, transitioning our fast-scaling data environment from a functional BigQuery warehouse into a governed, AI-ready data platform. We are seeking a hands-on Data Engineer to serve as our principal engineering resource, bringing the discipline, documentation rigor, and modern tooling needed to harden and scale our data infrastructure for our next phase of growth.

Reporting to the SVP of Technology within the DevOps team, you will partner closely with two data analysts and our full-stack developers. You will take ownership of the data environment, modernize our existing transformation logic while building the semantic layers and RAG-compatible data stores that will power BRUNT’s next generation of intelligent, AI-driven applications.

HOW YOU’LL DO IT:

PLATFORM STABILIZATION & MODERNIZATION

• Logic Migration: Lead the knowledge transfer and stabilization of existing BigQuery stored procedures, with a strategic vision to migrate them to dbt over time.
• Infrastructure as Code: Utilize tools like Terraform to support reproducible, version-controlled environment provisioning across GCP projects.
• Version Control: Establish strict Git history and peer visibility practices so no critical data logic exists without documented context.

PIPELINE ENGINEERING & OPTIMIZATION

• ELT/ETL Pipelines: Build, maintain, and optimize robust data flows from critical source systems into Google BigQuery.
• Fivetran Administration: Own the health and optimization of 40+ source datasets, managing sync schedules and expanding coverage as new systems onboard.
• Design and implement scalable ingestion solutions for non-Fivetran data sources, including structured replacements for file-based ingestion methods.
• Performance Tuning: Implement table partitioning, clustering, and incremental load strategies across high-volume tables to optimize query performance and reduce compute costs.

QUALITY, GOVERNANCE & SECURITY

• Testing Frameworks: Implement validation checks, schema contracts, and anomaly detection to guarantee the accuracy of data reaching our gold tier.
• Data Security: Lead the PII field inventory and column-level security access controls to ensure strict CCPA compliance.
• Data Governance: Maintain a centralized data dictionary and field-level definitions that serve both technical and non-technical audiences.

AI ENABLEMENT & COLLABORATION

• Semantic Layer: Partner with Full Stack Developers to build a semantic layer over BigQuery, enabling governed, AI-queryable access to data domains.
• RAG Architecture: Build and optimize data stores for Retrieval Augmented Generation (RAG) to power BRUNT’s next generation of intelligent applications.
• Cross-Functional Support: Partner with data analysts to ensure gold-tier datasets are performant and well-structured for Looker Studio dashboards, managing your workflow via Jira within an Agile sprint cadence.
• Serve as the technical data engineering point of contact within the DevOps team, translating business-driven data requirements into engineering specifications and delivery plans.

WHAT YOU NEED TO SUCCEED:

• Experience: 4–7 years of data engineering experience with demonstrated ownership of production data pipelines, cloud warehouses, and ELT/ETL architectures.
• The BigQuery Core: Strong hands-on proficiency with Google BigQuery, including schema design, query optimization, partitioning, clustering, and GCP cost management.
• Data Ingestion & Coding: Advanced SQL skills (ability to audit and refactor complex legacy stored procedures) paired with proficiency in Python for API-based ingestion and automation.
• Tooling Stack: Deep experience administering managed ingestion platforms like Fivetran and a strong working knowledge of dbt for transformation layer testing and documentation.
• AI Architecture (Preferred): Familiarity with Retrieval Augmented Generation (RAG) data structures and experience building semantic layers for LLM or AI agent consumption.
• Governance & Security: Working knowledge of cloud data governance, including PII handling, column-level security, and access control implementation.
• Infrastructure & BI: Familiarity with Terraform for infrastructure-as-code and Looker Studio (or similar BI tools) to ensure gold-tier data yields performant reporting.
• The "Builder" Mindset: A proven track record of operating as a senior individual contributor in lean environments, with a knack for inheriting, auditing, and modernizing legacy data systems.
• Team Cadence: Experience working within Agile/Scrum sprint frameworks using Jira, alongside strong technical writing skills for mapping data lineage and runbooks.
• Logistics: Must be 18+ with full-time availability (including occasional off-hours support for critical pipeline incidents) and the ability to reliably commute to the office 4x per week