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Staff Data Engineer

ESPN (Disney)

Staff Data Engineer

ESPN (Disney)

nicasio

·

On-site

·

Full-time

·

2mo ago

必須スキル

Python

Docker

Kubernetes

PyTorch

Spark

Airflow

Machine Learning

Job Posting Title:

Staff Data Engineer:

Req ID:

10129825

Job Description:

The Skywalker Sound Development Group is seeking an experienced Data Engineer to specialize in the creation, management, and optimization of data pipelines to support cutting-edge AI/ML research. This is a critical role in preparing high-quality datasets for the training, retraining, and evaluation of machine learning models tailored to immersive and multichannel audio applications.

As a Data Engineer, you will focus on developing robust pipelines for processing complex media datasets, enabling AI/ML researchers to build transformative solutions for speech processing, style transfer, and source separation. Your work will directly contribute to creating innovative soundtrack workflows for global media production.

This role is considered Hybrid, which means the employee will work 2-3 days onsite at our Nicasio, CA office and occasionally from home.

What You'll Do

  • Design, implement, and maintain scalable, automated data pipelines for the ingestion, preprocessing, and transformation of large-scale audio datasets.

  • Ensure pipelines support efficient model training and retraining workflows, enabling continuous improvement of AI/ML models.

  • Collaborate with AI/ML researchers to define data requirements and integrate feedback to improve data pipeline functionality.

  • Develop advanced preprocessing techniques for immersive and multichannel audio formats (e.g., Dolby Atmos, high-order ambisonics).

  • Automate data cleaning, normalization, and augmentation processes to prepare datasets for various model architectures, including foundational models and transformers.

  • Integrate external datasets and APIs while ensuring compliance with legal and ethical data usage standards.

  • Monitor and optimize pipeline performance to handle complex and dynamic data structures effectively.

  • Create tools and workflows for annotating, labeling, and curating datasets, including the use of active learning methods.

  • Perform exploratory data analysis to uncover trends, validate dataset quality, and identify data gaps.

What We’re Looking For

  • Master’s Degree with preference for PhD in Data Engineering/Science, Computer Science, Signal Processing, or a related field.

  • 8+years of experience in data engineering or data science with a focus on building pipelines for AI/ML applications.

  • Proficiency in Python, with expertise in data manipulation libraries such as Pandas, Num Py, and Py Torch’s data utilities.

  • Hands-on experience with audio processing libraries and tools (e.g., Librosa, FFmpeg, SoX) for handling complex audio formats.

  • Familiarity with scalable pipeline tools like GitLab, Apache Spark, Airflow, or Luigi, and experience with containerized workflows (Docker, Kubernetes).

  • Strong understanding of data pipeline requirements for model training, retraining, and evaluation in iterative research workflows.

  • Experience with immersive and multichannel audio formats.

  • Knowledge of cloud-based platforms and tools for storage and processing, such as AWS S3, Redshift, or Google Big Query.

  • Strong problem-solving skills, with a proactive mindset for addressing evolving data challenges.

Preferred Qualifications

  • Experience integrating data pipelines with AI/ML workflows, including active learning and model retraining.

  • Familiarity with audio-specific datasets and metadata management strategies.

  • Knowledge of machine learning principles and how data quality impacts model performance.

  • Experience with distributed training pipelines and large-scale dataset processing.

  • Contributions to open-source projects or published research in the fields of data science or audio processing.

  • Experience with visualization tools (e.g., Tableau, Matplotlib) for quality assurance and exploratory data analysis.

  • Expertise in designing systems to support AI/ML model monitoring and retraining over time.

The hiring range for this position in Nicasio, CA is $170,500 to $228,600 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.

Job Posting Segment:

Skywalker Sound

Job Posting Primary Business:

Skywalker Sound-Engineering

Primary Job Posting Category:

Data Engineering

Employment Type:

Full time

Primary City, State, Region, Postal Code:

Nicasio, CA, USA

Alternate City, State, Region, Postal Code:

Date Posted:

2025-09-16

総閲覧数

0

応募クリック数

0

模擬応募者数

0

スクラップ

0

ESPN (Disney)について

ESPN (Disney)

The happiest place on earth.

1,001-5,000

従業員数

Bristol

本社所在地

レビュー

3.7

10件のレビュー

ワークライフバランス

2.8

報酬

4.0

企業文化

3.8

キャリア

2.5

経営陣

2.5

65%

友人に勧める

良い点

Great benefits and competitive compensation

Supportive team and team spirit

Innovative and interesting projects

改善点

Long hours and overwhelming workload

Work-life balance issues

High expectations and tight deadlines

給与レンジ

435件のデータ

Junior/L3

Mid/L4

Junior/L3 · Content Associate

78件のレポート

$54,118

年収総額

基本給

$50,664

ストック

-

ボーナス

$3,454

$37,430

$78,777

面接体験

1件の面接

難易度

3.0

/ 5

期間

14-28週間

面接プロセス

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

よくある質問

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Past Experience