Sr Data Engineer

The Walt Disney Company (France); Santa Monica (CA); On-site; USD 142,000 - 190,000; Full time

Job summary

The Walt Disney Company in Santa Monica, CA, is seeking a Senior Data Engineer to design, build, and optimize data pipelines that support acquisition reporting and marketing analytics. You will work across AWS, Databricks, Unity Catalog, Snowflake, and Airflow to deliver reliable, scalable data platforms.

Collaborating with product, analytics, and marketing partners, you will ensure data accuracy, meet SLAs, mentor junior engineers, and contribute to engineering standards and roadmaps.

Qualifications

• 5+ years of experience as a Data Engineer or similar role.
• Strong proficiency in SQL (analytical SQL, complex joins, window functions).
• Hands‑on experience with PySpark and/or Spark SQL in production.
• Strong understanding of data modeling, ETL/ELT design patterns, and distributed data processing.
• Experience building pipelines in Databricks, including Delta Lake, Unity Catalog, data governance, and Lakehouse patterns.
• Strong experience in AWS (S3, IAM, EC2, Glue, Lambda, or related services).
• Proficiency with Airflow or similar orchestration tools.
• Experience building robust ingestion pipelines and working with semi‑structured formats (JSON, Parquet, CSV).
• Experience with Git/GitHub, CI/CD, and modern DevOps practices.
• Excellent communication skills and ability to work with cross‑functional partners.
• Bachelor’s degree in computer science, Information Systems or related field

Responsibilities

• Architect, build, and maintain scalable ETL/ELT pipelines for acquisition reporting using Databricks, PySpark, SQL, and Unity Catalog.
• Lead the modernization effort to migrate existing Snowflake‑based SQL scripts and transformations into Databricks UC with best practices in governance and structured access.
• Design robust ingestion frameworks for marketing vendor data.
• Implement data quality checks, monitoring, and automated remediation using Databricks, Snowflake, Airflow, and internal frameworks.
• Develop metadata‑driven, parameterized pipeline components to accelerate onboarding of new vendors and datasets.
• Partner with the Data Reliability Engineering team to integrate SLA‑based incident detection, logging, alerting, and auto‑recovery workflows.
• Collaborate with analytics and marketing stakeholders to understand reporting needs and ensure reliable dashboard data.
• Improve pipeline performance, reliability, logging, and observability.
• Contribute to engineering best practices, code reviews, technical design docs, and framework enhancements.
• Mentor junior engineers and contribute to team‑wide architectural decisions.

Skills

SQL

PySpark

Data modeling

ETL/ELT design

Databricks

Delta Lake

Unity Catalog

AWS

Airflow

Git/GitHub

CI/CD

Communication

Education

Bachelor's degree in computer science or related field

Tools

Databricks

Delta Lake

Unity Catalog

Snowflake

AWS services (S3, IAM, EC2, Glue)

Airflow

Git/GitHub

Job description

Technology is at the heart of Disney’s past, present, and future. Disney Entertainment and ESPN Product & Technology is a global organization of engineers, product developers, designers, technologists, data scientists, and more – all working to build and advance the technological backbone for Disney’s media business globally.

The team marries technology with creativity to build world‑class products, enhance storytelling, and drive velocity, innovation, and scalability for our businesses.We are Storytellers and Innovators. Creators and Builders. Entertainers and Engineers. We work with every part of The Walt Disney Company’s media portfolio to advance the technological foundation and consumer media touch points serving millions of people around the world.

Here are a few reasons why we think you’d love working here:

Building the future of Disney’s media:Our Technologists are designing and building the products and platforms that will power our media, advertising, and distribution businesses for years to come.

Reach, Scale & Impact:More than ever, Disney’s technology and products serve as a signature doorway for fans' connections with the company’s brands and stories. Disney+. Hulu. ESPN. ABC. ABC News…and many more. These products and brands – and the unmatched stories, storytellers, and events they carry – matter to millions of people globally. Innovation:We develop and implement groundbreaking products and techniques that shape industrynorms, andsolve complex and distinctive technical problems.

Commerce, Data & Identity provides the core product management functions for areas crucial to Disney’s media businesses. These include initiatives and products that power digital commerce, identity, and growth, as well as those that reach uniquely across The Walt Disney Company enterprise, such as messaging and privacy, among others. Additionally, itis responsible forthe data engineering, science, and products for Disney Entertainment & ESPN, along with their interconnection with other parts of The Walt Disney Company.

About the Team

The Acquisition Marketing Engineering team owns the ingestion, modeling, and activation of acquisition and lifecycle marketing data across multiple platforms. We build and maintain large scale data pipelines that ingest vendor data (paid media, mobile attribution, search, social, display, email, and more), land it in cloud storage, and transform it into analytics‑ready datasets powering acquisition reporting tools, dashboards, and executive insights.

You will be a senior member of the engineering team driving multiple transformations end‑to‑end.

Role Summary

The Senior Data Engineer will design, build, and optimize data pipelines and transformation frameworks that support high‑visibility acquisition reporting and marketing analytics use cases. You will work across AWS, Databricks, Unity Catalog, Snowflake and Airflow to create reliable, scalable solutions for ingesting and modeling marketing platform data.

You will collaborate closely with product, analytics, marketing operations, and stakeholder teams to ensure data accuracy, reliability, SLAs, and transparency for downstream dashboards.

Key Responsibilities

• Architect, build, and maintain scalable ETL/ELT pipelines for acquisition reporting using Databricks, PySpark, SQL, and Unity Catalog.
• Lead the modernization effort to migrate existing Snowflake‑based SQL scripts and transformations into Databricks UC with best practices in governance and structured access.
• Design robust ingestion frameworks for marketing vendor data.
• Implement data quality checks, monitoring, and automated remediation using Databricks, Snowflake, Airflow, and internal frameworks.
• Develop metadata‑driven, parameterized pipeline components to accelerate onboarding of new vendors and datasets.
• Partner with the Data Reliability Engineering team to integrate SLA‑based incident detection, logging, alerting, and auto‑recovery workflows.
• Collaborate with analytics and marketing stakeholders to understand reporting needs and ensure reliable dashboard data.
• Improve pipeline performance, reliability, logging, and observability.
• Contribute to engineering best practices, code reviews, technical design docs, and framework enhancements.
• Mentor junior engineers and contribute to team‑wide architectural decisions.

Basic Qualifications

• 5+ years of experience as a Data Engineer or similar role.
• Strong proficiency in SQL (analytical SQL, complex joins, window functions).
• Hands‑on experience with PySpark and/or Spark SQL in production.
• Strong understanding of data modeling, ETL/ELT design patterns, and distributed data processing.
• Experience building pipelines in Databricks, including Delta Lake, Unity Catalog, data governance, and Lakehouse patterns.
• Strong experience in AWS (S3, IAM, EC2, Glue, Lambda, or related services).
• Proficiency with Airflow or similar orchestration tools.
• Experience building robust ingestion pipelines and working with semi‑structured formats (JSON, Parquet, CSV).
• Experience with Git/GitHub, CI/CD, and modern DevOps practices.
• Excellent communication skills and ability to work with cross‑functional partners.
• Bachelor’s degree in computer science, Information Systems or related field

Preferred Qualifications

• Master’s degree in computer science, Information Systems or related field a plus
• Experience with marketing or customer acquisition data (Meta, Google Ads, Google CM360, TikTok, Twitter, Snapchat, Branch, AppsFlyer, Salesforce, etc.).
• Familiarity with data observability, SLA monitoring, incident workflows, or reliability engineering concepts.
• Exposure to data quality frameworks (Great Expectations, Deequ, Monte Carlo, or custom frameworks).

The hiring range for this position in Santa Monica, California is $141,900 to $190,300 per year, in New York, New York is $148,700 to $199,400 per year, and in Seattle, Washington is $148,700 to $199,400 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job‑related knowledge, skills, and experience among other factors. A bonus and/or long‑term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.