Data Engineer

BlueThrone•Capon Bridge, WV

4d•Remote

About The Position

Data sits at the center of everything we do at BlueThrone - from retention analysis and pricing experiments to UA scaling and cohort profitability. The people who build the data layer aren't a support function; they're a force multiplier. As our Data Engineer, you'll own the infrastructure that turns raw events from millions of mobile users into trustworthy data the business runs on. You'll design and scale the pipelines, warehouses, and tooling that everything else sits on top of - from finance dashboards to UA decisions to product experimentation. You'll work side-by-side with analytics, product, and growth to make sure the stack stays fast, clean, and ahead of where the business is heading. This is a hands-on, builder-first role where you'll be the person who decides how data flows, where it lives, and how reliably it gets there.

Requirements

5+ years of hands-on data engineering experience (or a closely related role with heavy pipeline and infrastructure work).
3+ years with a cloud data warehouse (BigQuery preferred, Snowflake or Redshift also fine), understanding partitioning, clustering, and query costs.
2+ years of production dbt experience (dimensional and incremental models, custom macros, tests, reusable packages).
3+ years of Python for data work (pipelines, scripts, internal tooling).
3+ years with orchestration tools (Airflow, Dagster, or Prefect).
Real experience building and maintaining BI dashboards and their underlying infrastructure.
Clear, concise communication skills, including documentation and explaining trade-offs to non-technical stakeholders.
Strong sense of ownership and ability to work independently in a fast-paced remote environment.

Nice To Haves

Experience with mobile apps, gaming, or any high-volume event-driven data environment.
Familiarity with Kafka, Airbyte, or RudderStack for ingestion.
Familiarity with Metabase or willingness to learn it quickly.

Responsibilities

Design, build, and maintain scalable data architecture that keeps up with a fast-evolving portfolio of apps.
Own the end-to-end data lifecycle: ingestion, transformation, storage, and modelling.
Write clean, efficient Python to power reliable pipelines, orchestrated workflows, and internal tools.
Lead our dbt project on BigQuery, focusing on macros, tests, packages, and scalable structure.
Partner with analytics to ship Metabase dashboards and tools for self-serve data access.
Set the standard for data quality and reliability, monitor pipelines, and catch issues proactively.
Collaborate with product, growth, monetisation, and finance leads to understand their data needs.
Bring in best practices from the broader data engineering world and raise the bar across the team.