Data Engineer

Our Technology Portfolio and Business Management (TPBM) team provides strategic and operational support across the Disney Enterprise Technology & Data organization.

The Portfolio Management team manages technology business demand, portfolio planning, and resource management processes to ensure proper prioritization, project planning, and alignment of outcomes to the strategic goals of Enterprise Technology.

The Technology Business Management team provides strategic insights based on financial planning data, technology spend data and technology operational data to provide cost transparency and enable strategic decision-making based Enterprise technology spend.

Key Responsibilities

Design and Build Data Pipelines: Develop, automate, and maintain scalable data pipelines to bring together financial and operational data (GL, vendor invoices, headcount, budgets) from multiple enterprise sources into Snowflake.

Model and Structure Data: Partner with architects to develop robust data models and create semantic layers, enabling user- friendly, flexible reporting and analysis.

Implement Cost Allocation Logic: Write performant SQL and/or Python code that automates multi-layer allocation engines, cost pool processing, and service-level analytics.

Collaborate Across Borders: Work closely with product managers, finance teams, AI/ML engineers, and QA to deliver governed, high-quality solutions on schedule.

Automate and Optimize: Leverage workflow/orchestration tools (such as Snowflake Tasks, DBT, or Airflow) and adopt CI/CD/code versioning best practices for reliability and speed.

Ensure Data Quality & Auditability: Implement and maintain reconciliation processes, checks, and IT controls to meet Disney s high standards for trust, compliance, and transparency.

Support and Evolve: Provide operational and incident support, performance tuning, and assist with continuous improvement of Enterprise Data & Analytics infrastructure.

Strong hands-on experience with Snowflake, especially building data pipelines, designing and structuring data objects, creating data marts

Experience working with financial datasets (e.g., financial planning, actuals) was emphasized as highly valuable, though not strictly mandatory., 5+ years of experience as a Data Engineer, with emphasis on cloud data platforms (Snowflake strongly preferred).

Expertise in advanced SQL for data transformation & modeling (e.g., window functions, CTEs).

Working experience with Python for ETL/ELT, automation, or analytics.

Hands-on experience delivering robust, maintainable data pipelines for complex enterprise environments.

Prior experience developing financial cost models (Financial planning, financial spend, cost allocation & recovery, etc.)

Familiarity with workflow orchestration tools (DBT, Airflow, etc.).

Knowledge of financial, accounting, or technology operations systems and data such as SAP, Clarity, ServiceNow, Cognos Planning and other similar systems.

Demonstrated ability to work collaboratively in cross-functional teams.

Strong communication skills; experience writing documentation and partnering with non-technical partners

Preferred Qualifications

Familiarity with Generative AI tools such as Snowflake Cortex AI

Knowledge and experience working with Technology Business Management (TBM) framework and methodology

Strong understanding of corporate finance & accounting processes

Duration : Long Term Contract

Must work onsite hybrid starting week 1 (2 weeks max from the time of offer acceptance)

Zero exceptions will be made, as this is corporate policy - no delayed remote start, no remote work

2 days a week onsite, must be flexible up to 4 days a week onsite

The assignment is expected to run through the end of the year (approximately 6-7 months), with a potential opportunity for extension depending on project needs and phases.

The team is building a new Snowflake data platform, focused primarily on financial data ingestion and modeling.