AI-Driven Data Engineer for Multi-Tenant Analytics

powerdigitalmarketing; United States; Remote; USD 110,000 - 180,000; Full time

Job summary

Power Digital Marketing seeks an experienced data/analytics engineer to own the core data foundation for an AI-native growth agency. You will build pipelines, models, and data marts serving internal teams, clients, and AI initiatives across a large multi-tenant warehouse.

Responsibilities include designing scalable ingestion, modeling spend and conversions, delivering client-focused modeling, and creating semantic layers for AI-generated SQL.

Qualifications

• 3+ years in data or analytics engineering with production code experience.
• Deep dbt expertise including incremental models, tests, snapshots, and exposures.
• Strong Python and SQL for data pipelines and modeling.
• Solid Snowflake and cloud data stack experience, preferably GCP.
• Experience modeling in a multi-tenant environment and integrating marketing datasets.

Responsibilities

• Own the core data foundation from raw data to serving layers.
• Build ingestion resilient to API changes and data retroactivity.
• Model across sources to reconcile spend, conversions, revenue across platforms.
• Deliver client-specific modeling atop shared patterns.
• Create semantic layers and metrics for AI-generated SQL consistency.
• Incorporate AI-agentic workflows to accelerate development and standardize patterns.
• Monitor data quality and optimize pipelines for cost and performance.

Skills

Python

SQL

dbt

Snowflake

Data pipelines

GCP

Tools

GitHub Copilot

CI/CD

Job description

Power Digital Marketing seeks an experienced data/analytics engineer to own the core data foundation for an AI-native growth agency. You will build pipelines, models, and data marts serving internal teams, clients, and AI initiatives across a large multi-tenant warehouse.

Responsibilities include designing scalable ingestion, modeling spend and conversions, delivering client-focused modeling, and creating semantic layers for AI-generated SQL.