Data Engineer - Martech

Hard Rock Digital•United States, FL

2d•Hybrid

About The Position

Hard Rock Digital is building a team focused on becoming the best online sportsbook, casino, and social casino company in the world. They are seeking individuals passionate about learning, operating, and building new products and technologies for millions of consumers, with a focus on customer interaction, experience, behavior, and insights. Hard Rock Digital leverages the established global brand of Hard Rock and the Seminole Tribe of Florida to enter the digital space. The Martech Data Engineer will work on the batched, warehouse side of CRM and marketing data within the Martech Engineering team. This role involves building and maintaining dbt models on Snowflake and running reverse-ETL (RETL) syncs to push modeled traits and audiences to marketing tools. This is a hands-on, mid-level engineering position where the individual will own specific areas of the warehouse, including models, tests, and RETL syncs, taking pipelines from request to production, ensuring their daily health, and gradually expanding ownership.

Requirements

2–4 years of professional experience in data engineering, analytics engineering, or a martech / digital analytics environment.
Strong SQL skills, including the ability to write and reason about non-trivial joins, aggregations, window functions, and CTEs, with a solid understanding of query execution.
Hands-on RETL/ETL experience, specifically with tools like Segment RETL, Hightouch, or Census for activating warehouse data into marketing and ad destinations.
Hands-on dbt experience, including building and maintaining models, tests, and documentation in a production environment.
Experience building on a cloud data warehouse, preferably Snowflake (BigQuery / Redshift experience is transferable).
Familiarity with the Segment ecosystem (or a comparable CDP) and understanding of how event data feeds into the warehouse.
Comfort with Git-based workflows for data management.
Experience with an orchestrator such as Airflow, dbt Cloud jobs, or Prefect.
A working understanding of how marketing tools utilize data, including CDPs, marketing automation platforms (e.g., Braze), and ad platforms.

Nice To Haves

Python for data transformation, orchestration, or integration.
Exposure to marketing attribution concepts and related platforms (e.g., AppsFlyer / MMPs, ad platforms).
Experience with data quality / observability tooling (e.g., dbt tests, Monte Carlo).

Responsibilities

Build and maintain dbt models on Snowflake, progressing from well-scoped models under review to ownership of specific areas.
Own RETL syncs end-to-end: define, ship, and monitor reverse-ETL processes that activate modeled traits and audiences into marketing tools such as Braze, ad platforms (Google, Meta, Microsoft), Salesforce, and other destinations, and troubleshoot data landing issues.
Work within the Segment ecosystem to understand how events and sources feed the modeled data layer.
Write and maintain data tests, documentation, and lineage to ensure model trustworthiness and clarity for others.
Partner with stakeholders to translate business requirements into well-defined models and activation flows.
Monitor data quality and freshness on the martech layer to proactively identify and address data drift before stakeholders do.
Leverage technical skill, ownership of pipelines, and a willingness to continuously improve in a startup-like environment.