Senior Data Engineer
WME · Beverly Hills, CA · 1 mo ago
Information Technology$128k/yrFull-time
We need to output HTML fragment with sections: About the role? Actually the posting includes Position Summary, How This Team Works, Key Responsibilities, Required Qualifications, Preferred Qualifications, Pay (Hiring Rate Minimum/Maximum). Also maybe Benefits? Not mentioned. Schedule? Not mentioned. So we include sections with actual content: About the role (maybe Position Summary), How This Team Works, Responsibilities, Qualifications (maybe split Required and Preferred? Could combine but better separate? The instruction: use headings for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). We need to decide which sections to include based on content.
We have Position Summary -> could be "About the role". How This Team Works -> maybe "How the team works" but not in list; but we could treat as part of About the role? Probably better to include as its own section? The allowed headings list includes "About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule". No "How the team works". So we might incorporate that content into About the role or Responsibilities? The instruction: "Prefer a few substantive sections over many thin ones." So we could merge How This Team Works into About the role.
Responsibilities: we have Key Responsibilities with six pillars. Use
- .
Requirements: we have Required Qualifications. Could be "Requirements". Also Preferred Qualifications could be under "Qualifications" or "Skills"? The list includes Qualifications and Skills. We could put Required Qualifications under "Requirements", Preferred under "Qualifications" or "Skills". But we need to avoid thin sections. Maybe combine Required and Preferred into "Qualifications" with subheadings? But we cannot add extra headings beyond allowed? We could use
for section headings only; inside we can have
and
- . We could have a "Qualifications" section that includes both required and preferred, maybe separate paragraphs.
Pay: we have hiring rate min/max. So include Pay section.
Benefits: not mentioned, so omit.
Schedule: not mentioned, omit.
Skills: maybe we could include skills from qualifications? But we already have qualifications.
Thus sections: About the role (combining Position Summary + How This Team Works), Responsibilities, Qualifications (combining required and preferred), Pay.
We must not repeat job title as heading. No Job ID.
We must preserve all substantive information; do not invent or summarize away detail. Must not omit details. So we need to include all details from the posting within those sections.
We must remove boilerplate: EEO, equal opportunity, etc. Also remove application instructions (none). Also remove duplicated lines.
We need to ensure we keep all specifics: e.g., mention of WME Enterprise IT, SQL data estate, legacy SQL environment, etc. Also mention of specific names: Principal Enterprise Architect (#55), Senior DBA, Sr Manager, GRC. Also mention of global footprint, GDPR, CCPA, etc. Also mention of AI fluency, etc. Also mention of six operating foundations. Also mention of responsibilities pillars with details. Also required qualifications bullet list. Also preferred qualifications bullet list. Also pay rates.
We must not add placeholders like "commensurate with experience". Not present.
We must not create sections with filler.
Thus produce HTML:
- ... each pillar ...
About the role
... combined content from Position Summary and How This Team Works ...
ThenResponsibilities
Qualifications
Required Qualifications:
- ... required items ...
Preferred Qualifications:
- ... preferred items ...
Pay
Hiring Rate Minimum $127,500 annually (minimum will not fall below the applicable state/local minimum salary thresholds)
Hiring Rate Maximum $170,000 annually
Make sure to not include any extra tags like etc. Check for any repeated lines: The posting had duplicate EEO statements; we removed. Check for any mention of "Equal Employment Opportunity" etc removed. Check for any mention of "WME is an equal opportunity employer and encourages applications..." removed. Check for any mention of "Per local requirements and in the interest of transparency, the rate shown below reflects the prevalent current hiring range for this position." That's part of pay info; we can keep that sentence? It's substantive about pay range. It says "Per local requirements and in the interest of transparency, the rate shown below reflects the prevalent current hiring range for this position." That's relevant to pay. We can include it in Pay section. Also "Hiring pay rates are based on a number of factors, including location and may vary depending on job-related qualifications, knowledge, skills and experience. The company strives to provide locally competitive rewards packages, which include base rate along with, as applicable, short- and long-term incentives, growth and developmental opportunities, and robust benefits, such as health care, retirement, vacation and other paid time off, and additional offerings." This is also about pay/benefits. Benefits not specified but we can include as part of Pay section describing compensation. However we should not create Benefits section if not explicit. But we can include this description in Pay section as it's about compensation. It mentions benefits but not specific. It's okay to include in Pay section as it's part of compensation description. We must not invent details; we can include that paragraph as is. Thus Pay section may have multiple paragraphs. Now ensure we preserve all specifics: mention of "Senior Data Engineer owns and modernizes WME Enterprise IT's SQL data estate — the databases behind the custom applications the product and engineering teams build, the legacy SQL environment those applications run on, and the pipelines that turn that data into trusted, query-ready information for analytics and reporting." etc. Let's craft About the role paragraph(s). Combine Position Summary and How This Team Works. Position Summary text: "Position Summary The Senior Data Engineer owns and modernizes WME Enterprise IT's SQL data estate — the databases behind the custom applications the product and engineering teams build, the legacy SQL environment those applications run on, and the pipelines that turn that data into trusted, query-ready information for analytics and reporting. This role does not inherit a modern, greenfield data platform; it inherits a working legacy SQL environment and helps set and drive the strategy to stabilize and modernize it. The role manages and supports the databases behind the custom product and engineering applications, keeps that data highly available with sound disaster-recovery planning, and builds the pipelines and analytics-ready data that reporting and BI are built on. It brings deep SQL and SQL Server expertise, works within the enterprise data architecture standards set by the Principal Enterprise Architect, partners with the Senior DBA on the database estate — developing toward broader database ownership over time — and partners with the Sr Manager, GRC on data governance and privacy. WME operates across a global footprint spanning the Americas, EMEA, and APAC, so the role must know how to operationalize data-privacy and regulatory requirements — GDPR, CCPA, and regional equivalents — at the data layer. The data it delivers serves analytics, reporting, and — increasingly — AI. It is a deep-technical senior individual-contributor role without direct reports." How This Team Works text: "How This Team Works Enterprise IT runs on one idea: operational excellence — systems that just work, problems fixed at the root, and an engineering bar that keeps climbing. Trusted data is foundational to that, and this role holds the bar for it. Six operating foundations describe how the function works, and a Senior engineer here models all six. Service management, done right. Runs the SQL data estate as a dependable service with clear ownership, SLAs, and root-cause fixes.Continual improvement. Uses data-quality signals, usage, and business feedback to keep improving pipelines and reporting.AI fluency. Uses AI tooling fluently in data engineering, and builds the trusted data foundation the AI backbone relies on.Ownership and documentation. Owns the data estate and pipelines end to end and leaves data models, runbooks, and documentation that scale.Security and risk by default. Builds data quality, classification, and access control in by default, in partnership with governance.Clarity and influence. Translates business questions into data products, and partners credibly with architecture, governance, and the business." We need to keep the content exactly, but we can format as paragraphs. Now Responsibilities: list six pillars with details. We need to extract each pillar's content: Legacy SQL Estate — Support & Modernization - Support, stabilize, and maintain the legacy SQL databases behind the custom product / engineering applications — performance, reliability, and availability. - Help set and drive the strategy to modernize the legacy SQL environment — consolidation, upgrades, and migration toward a governed, better-managed data estate. - Partner with the Principal Enterprise Architect (#55) on the database and data side of legacy modernization. Data Pipelines & Integration (ELT) - Build and modernize pipelines from source systems — the custom applications, SAP, and business systems — into a governed data store. - Own pipeline orchestration and scheduling; engineer resilient, observable pipelines with clear failure handling and recovery. - Integrate SAP as a major source, in partnership with the SAP program. Data Modeling & Analytics-Ready Data - Build the data models and analytics-ready datasets that BI, reporting, and analytics are built on. - Provide well-structured, trustworthy data so the business and analysts can build their own reports — deliver the data behind the reports, not the reports themselves. - Serve analytics, reporting, and AI consumers of the data. High Availability & Disaster Recovery - Ensure the databases and data estate are highly available — redundancy, failover, and resilience matched to each system's criticality. - Own database backup, restore, and disaster-recovery planning and testing. - Set and meet recovery objectives (RTO / RPO) for critical data, in partnership with infrastructure and BCDR. Data Governance, Privacy & Regulatory Operationalization - Contribute at a foundational level to data governance — quality, classification, lineage, and stewardship — in partnership with the GRC function. - Operationalize data-privacy and regulatory requirements at the data layer — GDPR, CCPA, and regional equivalents — across WME's global footprint: data residency, retention, minimization, and support for data-subject rights. - Implement the data controls GRC defines, including SOX-relevant controls, and produce the supporting evidence. Database Depth & DBA Succession - Bring deep SQL Server administration to the estate — T-SQL, tuning, maintenance, and troubleshooting. - Develop database-administration depth through structured mentorship from the Senior DBA, growing toward broader database ownership over time. - Maintain runbooks, documentation, and knowledge transfer; apply AI-assisted engineering where it adds value. We need to preserve all that. Now Required Qualifications list: - 7+ years in data and/or database engineering, with progressive responsibility. - Deep SQL and SQL Server administration — T-SQL, query optimization, maintenance, and troubleshooting of application databases. - Experience modernizing legacy SQL / database environments — consolidation, upgrades, and migration. - Database high availability and disaster recovery — Always On / clustering, backup and restore, and recovery planning (RTO / RPO). - ELT / pipeline engineering and integration from multiple source systems, including databases behind custom applications. - Data modeling and analytics-ready datasets; Power BI semantic models / datasets (the data layer behind reports) a plus. - Foundational data governance, and experience operationalizing data-privacy regulation — GDPR, CCPA, or equivalents — at the data layer (residency, retention, subject rights). Preferred Qualifications list: - Microsoft certifications — Azure Database Administrator (DP-300), Azure Data Engineer (DP-700 / DP-203), or SQL Server administration. - Data-privacy certification (e.g., IAPP CIPP/E or CIPP/US) or hands-on GDPR / CCPA operational experience. - Database HA/DR technologies (Always On, log shipping, replication) and backup / recovery