What are we building?
Hard Rock Digital is a fiercely focused team working to become the best online sportsbook, casino, and social gaming company in the world. We're building a deeply curious team with a passion for learning, operating, and building new products and technologies for millions of consumers. We're customer-obsessed — we care about each customer interaction, experience, behavior, and insight, and strive to ensure we're always acting authentically.
Rooted in the kindred spirits of Hard Rock and the Seminole Tribe of Florida, Hard Rock Digital taps a brand known the world over as the leader in gaming, entertainment, and hospitality. We're taking that foundation of success and bringing it to the digital space - ready to join us?
What's the position?
Hard Rock Digital's reporting lives across a range of tools and platforms, and this role owns the standard for what makes that reporting trustworthy and builds the modeled data layer where that standard is enforced: the definitions, dbt models and tests, and certification process that ensure the data behind every report means what it's supposed to mean.
In the first 12 to 18 months, you'll lead the migration of our reporting estate as the onramp to the role: assessing existing dashboards across Salesforce, Tableau, and ADAM, our Snowflake-native analytics platform, migrating what's eligible, and rebuilding it to a higher visualization standard on properly modeled data rather than dashboard-level logic. This work is how you build the institutional knowledge to govern the data well, not the whole of the job.
From there, data governance and the modeled layer underneath it become your core, ongoing function. The framework you build, and the dbt models that implement it, become the standard the wider BI Operations team builds against going forward. As it matures, dashboard builds and rebuilds become shared across the team rather than sitting solely with this role.
This role reports directly to the Senior Manager, Operations Strategy & Insights, and sits within BI Operations.
Responsibilities
Data governance and data modeling (ongoing, core function)
Own the data governance framework for ADAM: standards, naming conventions, definitions, documentation, and the certification process that ensures new data added to the platform is accurate and trustworthy before anyone relies on it
Build and own the certified data layer in dbt: the models, tests, and documentation that make governance a property of the warehouse itself rather than a document describing it
Act as the certification gate for new data while the framework is being established: when a business team or analyst wants to add new metrics, dimensions, or tables to the reporting environment, you partner with the BI Ops team to review, validate, and certify them, implementing the checks as dbt tests wherever they can be automated, or flag what needs to be fixed before they can be trusted
Maintain data lineage so anyone can trace where a number comes from, how it's calculated, and whether it's been certified — generated from the dbt project itself rather than kept as a separate catalogue that drifts
Monitor the health of the data environment over time: use automated testing and source freshness checks to catch when certified data drifts from its defined behavior, flag upstream changes that affect downstream reporting, and maintain trust in the platform as it grows
Partner with the data engineering team on schema changes, new source integrations, and pipeline updates that affect the reporting layer, owning the transformation layer that sits downstream of their pipelines
Partner with BI Operations leadership to define how governance responsibility transitions to the broader team once the framework is established and proven
Migrating and building reporting (first 12–18 months)
Evaluate reporting across all platforms in use — Salesforce, Tableau, and others — and determine the right destination and format for each based on underlying data structure and business need
Migrate eligible reporting into ADAM, landing each report or dataset where it actually fits best rather than defaulting to a like-for-like rebuild, and building the dbt models underneath it so the business logic lives in the warehouse layer rather than in the dashboard
Improve and consolidate as you go: spot overlap and redundancy across the reporting landscape before diving into individual migrations, so consolidation happens by design rather than dashboard by dashboard
Build every migrated report to a best-in-class visualization standard, with clear documentation of what it shows, how each figure is calculated, and where the underlying data comes from
Identify data gaps or modeling issues that stand in the way of a clean migration — resolving in dbt what belongs in the reporting layer, and translating the rest into specific asks the data engineering team can act on
Run stakeholder review and sign-off on each migrated report before the legacy version is retired
Recognize when a tool is being used for something it's not actually built for, and propose a better-fit alternative
What are we looking for?
3-6 years in BI or analytics, including at least a year hands-on with dbt: building and maintaining models against a cloud data warehouse, with a working understanding of materializations, testing, and how a modeled layer should be structured
Best-in-class visualization skill: has an eye for what makes a report actually clear and usable, not just accurate
A strong sense of how underlying data is structured and modeled, so you can reason about which platform or format actually fits a given dataset
The ability to look at what a report in one system is built to show and reconstruct that logic cleanly in another. This matters more than deep experience with any one specific tool
Strong SQL: enough to write and optimize the transformations behind a modeled layer, not only to trace and validate data lineage across systems
Data analytics engineering fundamentals: building tables for analytics, not only dashboards on top of them — dimensional design, how a warehouse layers from raw sources through to reporting-ready tables, and what makes a model perform at scale on any modern cloud platform. Comfortable working in version control (git) as part of a normal development workflow
Comfortable owning a large, ambiguous modernization effort and making informed calls along the way
Strong written communication: the documentation and certification work requires you to explain complex data logic clearly to people who aren't analysts
Bachelor's degree in Analytics, Business, Statistics, or a related field, or equivalent work experience
Preferred Skills
Direct experience with Snowflake, since ADAM is Snowflake-native
Experience introducing or maturing dbt practice on a team: testing standards, CI checks, model naming and folder structure
Experience with data governance frameworks, data dictionaries, or certification processes in a BI context
Exposure to lightweight or self-serve reporting tools (for example, Streamlit) as an alternative to traditional dashboards
Experience in iGaming, online sportsbook, casino, or another regulated digital industry
What’s in it for you?
We offer our employees more than just competitive compensation. Our team benefits include:
Competitive pay and benefits
Flexible vacation allowance
A hybrid / remote working environment
Startup culture backed by a secure, global brand
Roster of Uniques
We care deeply about every interaction our customers have with us, and trust and empower our staff to own and drive their experience. Our vision for our business and customers is built on fostering a diverse and inclusive work environment where regardless of background or beliefs you feel able to be authentic and bring all your talent into play. We want to celebrate you being you (we are an equal opportunity employer).