Senior Data Engineer - Enterprise DWH

Build and maintain data pipelines

• Build, enhance and troubleshoot ETL/ELT pipelines using SQL and Python.
• Transform raw operational data into clean, reusable datasets for reporting and analytics.
• Create data quality checks, reconciliation logic, logs and restartable processing steps.

Work with real business systems

• Integrate data from Casino/CMS, Opera PMS, Symphony/Micros POS, finance/ERP, loyalty and Microsoft 365 sources.
• Understand source-system changes and update mappings before reports break.
• Protect guest gaming and financial data through practical access control and careful data handling.

Own delivery, not just code

• Work with IT, business users and vendors to clarify requirements and turn them into working data solutions.
• Review vendor deliverables, source code, data mappings, test evidence and documentation before acceptance.
• Keep core knowledge in-house through clear documentation, reusable code and proper handover materials.
• Support production issues, investigate root causes and propose permanent fixes.

Improve performance and reliability

• Tune SQL queries, indexes, partitions and pipeline design for better speed and lower operational risk.
• Mentor junior or associate engineers through code review, pairing and practical troubleshooting.

• Experience: Ideally 3-5 years in data engineering, ETL/ELT, data warehouse or BI engineering. Candidates with 3+ years may be considered if they have strong hands-on delivery experience.
• Strong SQL for querying, transformation, troubleshooting and performance tuning.
• Good Python skills for data processing, automation or API-based integration.
• Hands-on experience building ETL/ELT pipelines and working with production data issues.
• Understanding data warehouse design, fact/dimension modeling and business reporting needs.
• Comfortably using Git, writing technical documentation and communicating with non-technical stakeholders.
• Experience with Azure Data Services, Microsoft Fabric, Databricks, Airflow, dbt, Spark or similar modern data platforms.
• Experience with Power BI datasets, semantic models or supporting reporting teams.
• Background in hospitality, casino/gaming, retail, loyalty, finance or other transaction-heavy environments.
• Working knowledge of business metrics such as ADR, RevPAR, Drop, Handle, Theo Win, Hold% or P&L reconciliation.