Data Engineer

Attention Arc•Durham, NC

4h•$90,000 - $120,000

About The Position

At Attention Arc, we exist to make media matter. As part of our Technology & Analytics team — The Builders and Translators — you build the connective tissue that powers everything we do. Your work ensures data flows cleanly, reliably, and intelligently across systems — turning complexity into clarity and infrastructure into impact. This Data Engineer role centers on architecting and scaling robust data pipelines for complex, well-documented datasets. You will design integrations that unify multiple data sources, create analysis-ready environments, and ensure our data warehouse is optimized for performance and growth. This is a hands-on role for someone who thrives in building elegant solutions to messy problems — and who understands that clean data is the foundation of credible insight.

Requirements

3–6+ years of experience in data engineering, data integration, or analytics engineering
Advanced proficiency in SQL and database design
Proven experience building and maintaining ETL/ELT pipelines across multiple data sources
Hands-on experience with Snowflake data warehouse architecture and optimization
Experience developing and maintaining DBT models for transformation workflows
Strong understanding of data modeling principles (relational and dimensional)
Experience implementing data quality validation and monitoring practices
Strong documentation habits and structured version control practices
Ability to translate business requirements into scalable technical solutions
Clear communicator who can explain complex systems in actionable terms
A disciplined approach to testing, validation, and long-term maintainability
Familiarity with orchestration tools (e.g., Airflow)

Nice To Haves

Background in media, advertising, or marketing analytics is preferred
Experience working with Nielsen or advanced measurement datasets is a plus
Experience building and maintaining APIs for data access and distribution
Experience working in cross-functional, agency-style environments

Responsibilities

Build & Scale Data Integrations
Develop and maintain scalable ETL/ELT pipelines integrating complex datasets from multiple internal and external sources
Build and maintain API endpoints to support secure, efficient data access and delivery
Design efficient SQL queries and optimized database structures that support analytics workflows
Ensure data transformations are documented, modular, and built for reuse
Architect Modern Data Infrastructure
Implement and optimize Snowflake data warehouse solutions for performance, scalability, and reliability
Design and maintain DBT (Data Build Tool) models to manage transformation logic and business rules
Create structured, well-documented data models that support clarity and cross-team adoption
Continuously improve pipeline performance, orchestration, and monitoring
Deliver Trusted, Analysis-Ready Data
Partner closely with Analytics, Planning, and Activation teams to deliver clean, validated datasets
Implement data quality checks, validation frameworks, and monitoring systems
Ensure consistency and reliability across all data integrations
Troubleshoot integration issues with urgency and precision
Improve, Automate & Evolve
Identify inefficiencies in workflows and proactively recommend scalable improvements
Standardize integration patterns to reduce complexity and onboarding friction
Evaluate new tools, frameworks, and approaches to enhance infrastructure capabilities
Contribute to documentation and best practices that elevate agency-wide data maturity