Job Description:
Position Overview
The primary responsibility of the Senior Data Engineer is to design, build, and maintain the data pipelines, lakehouse models, and analytics data services for casino management systems. This role requires strong technical expertise to deliver scalable, reliable, and high-performance data solutions within a modern Iceberg Data Lakehouse architecture that supports real-time processing, analytics, and reporting. Working under the guidance of the Lead Data Engineer, and reporting to the Director – Integration & Data, the Senior Data Engineer will own delivery of significant components of the platform and partner closely with the Data Portal and cross-functional application teams to ensure seamless integration and data flow across various systems.
All duties are to be performed in accordance with departmental and Las Vegas Sands Corp.’s policies, practices, and procedures. All Las Vegas Sands Corp. Team Members are expected to conduct and carry themselves in a professional manner at all times. Team Members are required to observe the Company’s standards, work requirements and rules of conduct.
Essential Duties & Responsibilities
- Design, build, and maintain components of the Iceberg Data Lakehouse using Apache Iceberg, Dremio, and Apache Polaris, contributing to architectural decisions on scalability, security, and future extensibility.
- Develop and maintain complex data pipelines using Python and Apache Kafka for efficient data ingestion, transformation, and storage into Iceberg tables, ensuring high availability and data quality.
- Build and maintain the curated data models and semantic layer in Dremio that power interactive dashboards, canned reports, self-service analytics, and scheduled data exports.
- Build and maintain the data access layer that serves lakehouse data to downstream consumers, supporting JSON and CSV export formats for use cases such as regulatory reporting (e.g., DICJ access).
- Implement integrations with diverse data sources (e.g., transactional systems, third-party APIs, IoT devices) through Kafka event streaming and Dremio query federation to create a unified data ecosystem for the casino management system.
- Implement data ingestion and transformation processes within a Lambda-Kappa hybrid architecture that supports both batch and real-time analytics, optimizing data movement and processing efficiency.
- Develop and maintain PostgreSQL database schemas and queries to support application state, metadata management, and analytical workloads.
- Apply and help enforce data governance policies and best practices using Dremio and Polaris governance capabilities to ensure compliance with regulatory standards, data security, and privacy protocols.
- Work closely with data analysts, data scientists, and business stakeholders to understand data requirements and deliver high-quality solutions — including embedded Metabase dashboards and the datasets behind portal features — that enable data-driven decision-making.
- Monitor and optimize data pipeline performance using Prometheus and Grafana, identifying bottlenecks and implementing enhancements to ensure rapid data processing and retrieval.
- Mentor junior and mid-level data engineers through code review, pairing, and knowledge sharing, promoting best practices in data engineering.
- Use Claude Code in day-to-day engineering work — developing and refactoring pipeline code, writing tests, and documenting existing codebases — applying sound judgment to review and verify AI-generated output before it reaches production.
- Maintain comprehensive documentation of data models, data contracts, workflows, and processes to support ongoing development and operational maintenance.
- Perform job duties in a safe manner.
- Attend work as scheduled on a consistent and regular basis.
- Perform other related duties as assigned.
Minimum Qualifications
- At least 21 years of age.
- Proof of authorization to work in the United States.
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
- Must be able to obtain and maintain any certification or license, as required by law or policy.
- 5+ years of experience in data engineering, including demonstrated ownership of end-to-end pipelines in production; experience in the gaming or casino industry preferred.
- Strong hands-on experience with Apache Kafka for real-time event streaming and data pipeline development.
- Familiarity with Apache Iceberg table formats preferred, including partitioning strategies, schema evolution, and snapshot management.
- Hands-on experience with a modern distributed SQL query engine (e.g., Dremio, Starburst/Trino, StarRocks) for analytics, reporting, and query federation across heterogeneous data sources; Dremio experience strongly preferred.
- Demonstrated experience building semantic layers, reflections, and curated views in Dremio (or similar) to support reporting and self-service analytics.
- Strong working knowledge of PostgreSQL (16+) including query optimization, indexing strategies, and schema design for both application and analytical workloads.
- Demonstrated experience with Iceberg catalog management (e.g., Apache Polaris, Lakekeeper) and object storage (e.g., AWS S3, MinIO) for physical data file management.
- Familiarity with cloud data solutions (e.g., AWS, Azure) and with deploying data services on Kubernetes using Docker containers.
- Strong programming skills in Python (3.11+) for developing data pipelines, ingestion frameworks, and data processing workflows, with familiarity in libraries such as PyIceberg, PyArrow, and Pydantic.
- Solid experience with data modeling techniques (e.g., star schema, snowflake schema) to support complex analytics and reporting requirements.
- Demonstrated experience with data quality frameworks and tools to ensure data integrity and compliance with business standards.
- Working knowledge of CI/CD practices using GitHub Actions for automating build, test, and deployment processes.
- Experience with monitoring and observability tools (e.g., Prometheus, Grafana) for pipeline and application health monitoring.
- Familiarity with BI tools (e.g. Metabase, Tableau, PowerBI).
- Strong analytical and problem-solving abilities with a focus on delivering high-quality data solutions.
- Experience mentoring less experienced engineers and contributing to a culture of knowledge sharing and continuous improvement is preferred.
- Strong interpersonal skills with the ability to communicate effectively and interact appropriately with management, other Team Members and outside contacts of different backgrounds and levels of experience.
Physical Requirements
Must be able to:
- Physically access assigned workspace areas with or without reasonable accommodation.
- Work indoors and be exposed to various environmental factors such as, but not limited to, CRT, noise, and dust.
- Utilize laptop and standard keyboard to perform essential functions of the job.