Lead Data Engineer

Lead Data Engineer

Requirements

• 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, with at least 2 years in a lead or senior role, preferably in the gaming or casino industry.
• Hands-on experience with on-premise Data Lake data pipelines, including storage component (HDFS, Cassandra), compute component (Spark), message component (Kafka).
• Experience with on-premise and Data Lakehouse technologies (Iceberg, Dremio, Flink, AWS Lake Formation, AWS Glue, AWS Athena, Azure Databricks-Unity Catalog, Azure Synapse, Microsoft Fabric Lakehouse).
• Proficiency with data pipeline technologies (e.g., Apache Kafka, Apache Airflow, Apache NiFi) for orchestrating data workflows.
• Demonstrated experience with ETL frameworks and tools (e.g., Talend, Informatica, AWS Glue) for data integration and processing.
• Strong knowledge of relational and NoSQL databases (e.g., PostgreSQL, MongoDB, Cassandra) and experience with data warehousing concepts.
• Familiarity with cloud data solutions (e.g., AWS, Azure, Google Cloud) and their associated data services (e.g., AWS Redshift, Google BigQuery).
• Proficiency in programming languages commonly used for data engineering (e.g., Python, Java, Scala) for building data pipelines and processing workflows.
• Understanding of data modeling techniques (e.g., star schema, snowflake schema) to support analytics and reporting needs.
• Demonstrated experience with data quality tools and frameworks to ensure data integrity and compliance.
• Knowledge of continuous integration/continuous deployment (CI/CD) practices and tools (e.g., Jenkins, GitLab CI) for automating data pipeline deployment.
• Strong analytical and problem-solving skills with a focus on delivering high-quality data solutions.
• Proven ability to lead and mentor junior data engineers, fostering a culture of knowledge sharing and continuous improvement.
• 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.

Responsibilities

• Design, develop, and maintain robust data pipelines that support data ingestion, transformation, and storage, ensuring high data quality and reliability.
• Lead the integration of diverse data sources (e.g., transactional systems, third-party APIs, IoT devices) to create a unified data ecosystem for the casino management system.
• Implement and optimize Extract, Transform, Load (ETL) processes to ensure efficient data movement and processing for both batch and real-time analytics.
• Collaborate with the Principal Data Architect to establish the overall data architecture, ensuring it meets business needs and supports future scalability.
• Develop and implement data quality checks and monitoring processes to ensure accuracy and consistency across all data sources.
• Work closely with data analysts, data scientists, and business stakeholders to understand data requirements and deliver solutions that enable data-driven decision-making.
• Monitor and optimize data pipeline performance, identifying bottlenecks and implementing improvements to enhance data processing speeds.
• Maintain comprehensive documentation of data engineering processes, architecture, and workflows to support ongoing development and maintenance.
• Perform job duties in a safe manner.
• Attend work as scheduled on a consistent and regular basis.
• Perform other related duties as assigned.

Preferred Qualifications

No preferred qualifications provided.