Principal Analytics Engineer

Scientific Games • Alpharetta, GA

1d

About The Position

Scientific Games: Scientific Games is the global leader in lottery games, sports betting and technology, and the partner of choice for government lotteries. From cutting-edge backend systems to exciting entertainment experiences and trailblazing retail and digital solutions, we elevate play every day. We push game designs to the next level and are pioneers in data analytics and iLottery. Built on a foundation of trusted partnerships, Scientific Games combines relentless innovation, legendary performance, and unwavering security to responsibly propel the global lottery industry ever forward. Position Summary As the Principal Analytics Engineer, you are the lead architect and technical authority for Data & AI Platform. Your primary objective is to transform raw data at the Bronze Layer into high-performance, production-grade assets in the Silver and Gold layers on Databricks. You will be responsible for the "Strategic Handshake" with upstream engineering, ensuring that downstream Data science, Business Analytics and Data Products workstreams are effectively decoupled and unblocked to drive immediate commercial value and topline growth.

Requirements

• Professional Track Record: 10+ years of experience in Data Engineering, Architecture, or Analytics Engineering, with a significant history of building enterprise-scale data products.
• Databricks Mastery: Expert-level knowledge of Databricks, Spark, and cloud-native environments (AWS/Azure).
• Advanced Engineering Skills: Proficiency in Python, SQL, and modern ETL/ELT patterns. Experience with containerization (Docker) and Linux server administration is essential.
• Architectural Vision: Proven ability to decouple complex data systems and move away from vendor-dependent or manual legacy workflows.
• Analytical Depth: Strong mathematical foundation to support econometric modeling, forecasting, and statistical validation efforts.

Responsibilities

• Platform Architecture & Governance: Lead the design and implementation of the analytics engineering function. Establish rigorous governance standards, documentation frameworks, and a centralized team knowledge hub to standardize business logic and metrics across the organization.
• Databricks Ecosystem Leadership: Serve as the Subject Matter Expert (SME) for the Databricks platform. Architect and manage the Medallion architecture (Bronze, Silver, Gold), ensuring secure landing zones, optimized schemas, and reliable data transformation pipelines.
• Orchestration & Automation: Modernize the data lifecycle by implementing advanced, DAG-based orchestration tools (e.g., Mage, Airflow) to eliminate manual intervention and legacy dependencies (e.g., Alteryx). Build automated audit and check systems to ensure high pipeline reliability.
• Self-Service Democratization : Architect and maintain a robust Semantic Layer that translates complex technical schemas into a "business-language" interface. Your goal is to empower non-technical stakeholders in regional markets build their own reliable insights with 100% confidence in the underlying "Gold Layer" logic, effectively removing the engineering team as a reporting bottleneck.
• Commercial Asset Engineering: Partner with Data Product Owners to translate complex commercial requirements into technical table specifications and relational structures.
• Performance Optimization: Act as a technical force multiplier by refactoring legacy data sources to improve load times and efficiency for executive BI tools targeting performance gains.
• Technical Mentorship & Standards: Set the "Golden Path" for engineering excellence. Provide technical leadership through code reviews, architectural oversight, and mentoring of multi-disciplinary teams to ensure all builds are scalable, decoupled, and production-ready.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 251-500 employees