Data Engineer - Martech

Hard Rock Digital•United States, FL

18h•Hybrid

About The Position

Reporting into the Martech Engineering team, the Martech Data Engineer works on the batched, warehouse side of our CRM and marketing data. You'll build and maintain dbt models on Snowflake and run the reverse-ETL (RETL) syncs that push modeled traits and audiences back out to the marketing tools our partners act on. This is a hands-on mid-level engineering role. You'll own your own well-bounded areas of the warehouse — models, tests, and the RETL syncs that activate them — take pipelines from request to production, keep them healthy day to day, and grow toward owning more of the layer over time.

Requirements

2–4 years of professional experience in data engineering, analytics engineering, or a martech / digital analytics environment.
Strong SQL — a hard requirement. You can write and reason non-trivial joins, aggregations, window functions, and CTEs, and you understand what a query is doing.
Hands-on RETL/ETL experience. Segment RETL, Hightouch, Census, or similar — activating warehouse data into marketing and ad destinations.
Hands-on dbt experience — you've built and maintained models, tests, and documentation in a real project.
Experience building on a cloud data warehouse, ideally Snowflake (BigQuery / Redshift experience transfers).
Familiarity with the Segment ecosystem (or a comparable CDP) and how event data feeds the warehouse.
Comfort with Git-based workflows for data, and an orchestrator (Airflow, dbt Cloud jobs, Prefect, or similar).
A working understanding of how marketing tools use data — CDPs, marketing automation (Braze or similar), and ad platforms.

Nice To Haves

Python for transformation, orchestration, or integration of work.
Exposure to marketing attribution concepts and the platforms behind them (AppsFlyer / MMPs, ad platforms).
Experience with data quality / observability tooling (dbt tests, Monte Carlo, or similar).
A developing problem-solver — you check lineage and compare source vs. modeled data before changing things, and you know when to work independently and when to pull in the senior engineer.
A clear communicator who can explain a model or discrepancy to a non-technical marketing, ops, or CRM partner.
Curious and self-aware — eager to dig into platforms you haven't seen and honest about what you don't know yet.
Someone who can hold competing priorities across a few stakeholders and keep their pipelines documented and healthy.

Responsibilities

Build and maintain dbt models on Snowflake — from well-scoped models under review toward ownership of your own areas.
Own RETL syncs end to end: define, ship, and monitor the reverse-ETL that activates modeled traits and audiences into Braze, ad platforms (Google, Meta, Microsoft), Salesforce, and other destinations — and troubleshoot when data doesn't land as expected.
Work in the Segment ecosystem where the warehouse meets the CDP — understanding how events and sources feed the modeled layer.
Write and maintain data tests, documentation, and lineage so the models we ship stay trustworthy and the next person can follow them.
Partner with stakeholders to translate business requirements into well-bounded models and activation flows.
Watch data quality and freshness on the martech layer and help catch drift before a stakeholder does.
Because we operate with a startup mindset, we'll rely on your technical skill, your ownership over the pipelines you run, and your willingness to keep leveling up.