Sr. Data Engineer

The Walt Disney Company (Corporate); Buenos Aires; On-site; ARS 2,000,000 - 6,000,000; Full time

Job summary

The Walt Disney Company (Corporate) is seeking a Senior Data Engineer to build and maintain the data foundation for the D‑Fi AI finance platform. You will own ELT pipelines ingesting SAP, EPM, GL and operational data into a unified data layer with semantic definitions and certified metrics.

You will ensure pipeline reliability, data quality, and near‑real‑time data freshness while collaborating with finance and product teams to evolve the architecture and enable fast, trustworthy data access.

Qualifications

• 5+ années d’expérience en data engineering et création de pipelines ELT en production.
• Niveau avancé d’anglais requis.
• Diplôme de Bachelor en Informatique ou en Génie ; diplôme avancé apprécié.
• Expérience démontrée avec une couche sémantique ou un cadre de métriques certifié.
• Bonne connaissance des contrôles qualité et des patterns near‑real‑time / CDC.

Responsibilities

• Posséder la fondation data et les pipelines ELT ingestant SAP, EPM et GL, ainsi que des données opérationnelles dans la plateforme unifiée.
• Définir et maintenir la couche sémantique et les métriques certifiées servant de source unique de vérité.
• Maintenir la fiabilité des pipelines, les checks qualité et les chargements incrémentiels; mettre en place le CDC.
• Gérer la synchronisation de la hiérarchie organisationnelle et assurer que les métadonnées restent à jour.

Skills

Data engineering

English (Advanced)

Education

Bachelor’s degree in Computer Science or Engineering

Advanced degree preferred

Tools

dbt

Semantic layer

Certified metrics framework

Job description

Résumé du poste:

Job Requirements

BUILD SOMETHING BIGGER THAN YOURSELF

The Walt Disney Company, together with its subsidiaries and affiliates, is a leading diversified international family entertainment and media enterprise with the following business segments: Disney Entertainment, ESPN, Disney Parks, and Experiences and Products. From humble beginnings as a cartoon studio in the 1920s to its preeminent name in the entertainment industry today, Disney proudly continues its legacy of creating world-class stories and experiences for every member of the family. Disney’s stories, characters and experiences reach consumers and guests from every corner of the globe. With operations in more than 40 countries, our employees and cast members work together to create entertainment experiences that are both universally and locally cherished.

How you will contribute to our magical experience?

Disney Financial Insights (D-Fi) is a new platform reimagining how Finance teams and budget owners across Disney interact with financial data — replacing manual pulls, static reports, and email-driven approvals with one AI-powered, orchestrated experience built on top of Disney financial systems.

We're hiring the founding engineering team for this AI framework. One theme unifies every engineering role on D-Fi: autonomy and trust. You build the foundation that makes autonomous decisions trustworthy — the data platform every agent, model, and product capability on D-Fi depends on. You'll own the data foundation for D-Fi — the ELT pipelines, semantic layer, and certified metric logic that define what "budget," "actuals," and "variance" mean across every surface of the platform. As D-Fi moves toward autonomous finance, agents cannot operate on stale or untrusted data — this role is what makes that reliability possible.

Owns the data platform foundation that every agent, model, and product capability depends on. Builds and maintains ELT pipelines that ingest financial data from SAP, EPM, and GL systems, and operational data from Snowflake, HRIS, and procurement systems, into the unified data platform. Owns the dbt transformation models, semantic layer definitions, and certified metric logic — the single source of truth for what "budget," "actuals," and "variance" mean across every surface of the platform. Maintains pipeline reliability, data quality checks, incremental load strategies, and change data capture for near-real-time data freshness. Manages the org hierarchy sync that keeps cost center and leader metadata current as Disney's organization changes. As the platform evolves toward autonomous finance, ensures the data platform can support the low-latency, high-reliability data access that agentic workflows require — agents cannot operate on stale or untrusted data.

The Sr. Data Enginer will be responsible for:

Own the data foundation. Build and maintain ELT pipelines that ingest financial data from SAP, EPM, and financial systems, and operational data from Snowflake, HRIS, and procurement systems, into the unified data foundational layer. We don’t recreate those systems or duplicate data; we integrate with those systems. Own the semantic layer and certified metrics. Build and maintain the dbt transformation models and semantic layer definitions that serve as the single source of truth for what "budget," "actuals," and "variance" mean across every surface of the platform. Maintain pipeline reliability and data quality. Own data quality checks, incremental load strategies, and change data capture for near-real-time data freshness. Manage org hierarchy sync. Keep cost center and leader metadata current as Disney's organization changes, so downstream reporting and agent decisions stay accurate. Build for agentic-grade reliability. Ensure the data foundational layer can support the low-latency, high-reliability data access that agentic workflows require — agents cannot operate on stale or untrusted data.

What we need from you to be part of this story:

5+ years of data engineering experience, with a strong track record building and owning production ELT pipelines. Advanced level of English (must). Bachelor's degree in Computer Science, Engineering, or related field; advanced degree a plus but not required. Demonstrated experience building and maintaining a semantic layer or certified metrics framework that multiple teams or systems depend on. Strong data quality instincts — comfort building automated checks and catching issues before they reach downstream consumers. Experience with near-real-time or change-data-capture patterns, not just batch pipelines. Background working with financial or ERP data (SAP, EPM, GL systems) is a strong plus, but not required — genuine curiosity about the domain