Senior Engineer - Data DevOps

Hard Rock Digital

9d•Hybrid

About The Position

Hard Rock Digital is a team focused on becoming the best online sportsbook, casino, and social gaming company in the world. We’re building a team that resonates with passion for learning, operating and building new products and technologies for millions of consumers. We care about each customer's 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, the new 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? We are seeking an experienced Senior Engineer - Data DevOps who excels at architecting scalable data infrastructure, leading technical initiatives, and mentoring engineering teams. You'll work as a senior member of the Data DevOps team, driving strategic technical decisions while collaborating with Data Science, Machine Learning, Reporting, and other data-related teams to deploy and support cutting-edge data applications. This high-impact role will position you as a technical leader, shaping the future of our data infrastructure and establishing best practices across the organization.

Requirements

Bachelor’s degree in computer science, Information Technology, or a related field, or equivalent work experience. Master's degree preferred.
6+ years of experience in DevOps, DataOps, or similar roles, with at least 2 years in a senior or lead capacity.
Deep expertise in key technologies, including Airflow, Snowflake, SageMaker, DBT, and Databricks.
Strong architectural experience with AWS services and cloud-native design patterns.
Proven track record of leading technical projects and mentoring engineering teams.
Excellent communication, leadership, and interpersonal skills with demonstrated ability to influence technical direction.
Experience working in a fast-paced, high-velocity environment while managing multiple strategic priorities effectively.
Strong problem-solving skills with the ability to navigate ambiguity and make sound technical decisions.

Nice To Haves

Certifications in AWS/Snowflake/other technologies strongly preferred.

Responsibilities

Architect and lead the design of complex, enterprise-scale data pipelines using Airflow, DBT, and Databricks.
Define and implement strategies for pipeline performance optimization to support real-time and batch processing at scale.
Lead the design and optimization of AWS-based data infrastructure, including S3, Lambda, and Snowflake architecture
Establish and enforce best practices for cost-efficient, secure, and scalable data processing across the organization.
Design and optimize AWS SageMaker environments for ML teams, ensuring optimal performance and resource utilization.
Lead cross-functional collaboration with ML, Data Science, and Reporting teams to establish data strategy and ensure seamless data accessibility.
Design and implement comprehensive data pipeline monitoring, alerting, and logging frameworks to proactively detect failures and performance bottlenecks.
Architect automation solutions for data quality, lineage tracking, and schema evolution management.
Lead incident response efforts, performing complex troubleshooting and root cause analysis for critical data issues.
Champion and evolve Data DevOps best practices, driving automation, reproducibility, and scalability across the organization.
Mentor junior and mid-level engineers, conducting code reviews and providing technical guidance.
Establish technical standards, document complex infrastructure patterns, data workflows, and operational procedures.
Evaluate and recommend new technologies and tools to improve data infrastructure and workflows.