Lead Data Engineer - Delivery Lead(485388)
About the job you//'re considering
The Delivery Lead will oversee the end-to-end delivery of a Teradata-to-Azure/Databricks migration powering client//'s next-generation curated analytics platform as well as coordinate delivery across other data-related initiatives. This role sits onsite in Las Vegas and requires strong leadership across gaming, hospitality, F&B, entertainment, digital, and enterprise analytics domains. The Delivery Lead will coordinate client delivery teams, client//'s business stakeholders, and technology partners to modernize the data ecosystem supporting, but not limited to, guest personalization, resort operations, gaming analytics, revenue optimization, and enterprise decisioning.
This is a high-visibility professional-services leadership role responsible for predictable delivery, stakeholder alignment, and ensuring client realizes measurable value from its cloud analytics transformation.
Your role
Delivery Leadership & Governance
- Governance & Reporting — Establish disciplined delivery governance aligned to client//'s PMO, including RAID management, executive status reporting, dependency tracking, and operational readiness checkpoints.
- Stakeholder Management — Serve as a primary onsite interface for business and technology stakeholders, translating delivery progress, risks, and decisions into business-relevant language.
- Risk & Issue Management — Proactively manage risks tied to high-traffic resort periods, major entertainment weekends, operational dependencies, data quality, platform readiness, and downstream analytics adoption.
- Technical Program Leadership EDH 2.0 Migration Strategy — Oversee migration planning and execution for enterprise data warehouse workloads, including Teradata tables, views, SQL logic, stored procedures, ETL/ELT dependencies, and analytics consumption patterns.
- Azure Data Architecture — Guide delivery alignment to target-state Azure data architecture, including Azure Data Lake Storage, curated data zones, secure data-sharing patterns, and business-ready consumption layers.
- Databricks Delivery — Ensure Azure Databricks pipelines, Delta Lake patterns, and medallion-oriented engineering practices support scalable analytics, reporting, personalization, forecasting, and enterprise decisioning use cases.
- Data Analysis & Quality — Drive data profiling, reconciliation, validation, and KPI alignment across source and target platforms to support business confidence and production readiness.
- Team, Financial & Partner Management Onshore/Offshore Coordination — Manage Capgemini delivery teams across architecture, data engineering, data analysis, QA, lineage, data modeling, and release coordination.
- Resource Planning — Align capacity, skill mix, and work allocation to migration waves, delivery priorities, and business-domain sequencing.