Data Engineer

Hurrdat•Omaha, NE

12d•$80,000 - $90,000•Onsite

About The Position

We are seeking a Data Engineer to build and maintain the data models and pipelines behind Hurrdat's analytics and reporting. You will work primarily in Google BigQuery and dbt, designing the warehouse models that turn advertising, content, web, and search data into governed, well-documented tables that our reporting and client teams rely on every day. The role spans both paid media performance and content analytics, supporting how our teams measure organic content, SEO, and editorial work alongside advertising campaigns. This is a hands-on role with real ownership: you will design the models, write the transformations, build the pipelines that feed them, and own the datasets that reach our clients. It is well suited to someone with a strong SQL and data modeling foundation who wants to deepen their work in a modern data stack. This position reports directly to the Sr. AI/ML Engineer.

Requirements

Bachelor's degree in Computer Science, Data Science, Information Systems, Statistics, or a related field, or equivalent practical experience.
Demonstrated experience with data modeling, including dimensional modeling, normalization and denormalization tradeoffs, and layered warehouse design such as a medallion (bronze, silver, gold) architecture.
Proficiency in SQL, including joins, aggregations, window functions, common table expressions, and query troubleshooting.
Hands-on experience building transformations in dbt, including models, tests, and documentation.
Working knowledge of Python for scripting, data manipulation, and API integration.
Two to four years of experience in data engineering, analytics engineering, or business intelligence development.
Experience with a cloud data warehouse such as BigQuery, Snowflake, or Redshift.
Familiarity with Git-based version control and code review workflows.
Clear written and verbal communication, including the ability to explain technical issues to non-technical audiences.
Ability to work independently on well-scoped tasks, ask questions early, and manage competing priorities.

Nice To Haves

BigQuery experience is preferred.
Exposure to marketing, advertising, or content performance data sources is a plus.

Responsibilities

Design, build, and maintain data models that turn raw source data into clean, well-structured tables for reporting and analysis.
Develop, test, and document transformations in dbt, including model logic, data tests, and version-controlled code.
Build and maintain ELT pipelines that bring advertising, content, web, and search data from third-party platforms and APIs into the warehouse.
Write Python scripts to automate recurring data tasks and integrate with external APIs.
Monitor scheduled pipeline runs, investigate failures, and resolve data quality issues such as schema changes, missing data, and duplicate records.
Apply version control and code review practices, including branching, pull requests, and peer review, to all data code.
Support warehouse performance and cost management through partitioning, clustering, and query optimization.
Partner with reporting, analytics, content, and account teams to translate business questions into reliable datasets and clear documentation.
Maintain documentation of data sources, table definitions, and model logic so that others can understand and use the data independently.
Assist with data preparation and infrastructure supporting the organization's AI and machine learning initiatives.