Glendale, CA

Developer Jobs in Glendale, CA

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Today

Lead Product Software Engineer

Disney Entertainment and ESPN Product & Technology Glendale, CA

Glendale, CA

Today

$156k - $209k/yr Full time API APIs Cloud Operations

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Job Description

Lead full-stack product engineering to standardize guest-facing web delivery across Disney Entertainment and ESPN brands, from front-end rendering to APIs and cloud performance.

Responsibilities

Build, modernize, and own guest-facing web applications end to end, covering rendered front ends, backend services and APIs, identity integrations, and caching behavior for fast, reliable scale.
Define and execute a long-term technical strategy across brand sites, with emphasis on reliability, observability, and delivery aligned to business priorities.
Research and evangelize paved-path architecture patterns and engineering standards that apply across brands rather than per site.
Lead legacy stack migrations to current platforms by scoping work, sequencing against live traffic, and completing changes without guest-facing regression.
Lower engineering friction across the portfolio through tooling, debugging interfaces, deployment models, and automation that enable faster shipping with less risk.
Set standards for AI-assisted development, including review gates, validation, and observability to trust automation on critical paths.
Provide technical guidance and mentoring to senior engineers, run design reviews, and partner with P5-level Engineering Leads on stack standardization.
Own performance, scalability, and resiliency for mission-critical cloud services.
Support department-wide technical planning and manage technical risks for critical site projects.

Requirements

Minimum 7 years of relevant experience as a software engineer or architect.
Production experience shipping guest-facing web applications, including modern front-end frameworks such as React with TypeScript and server-side rendering, plus backend services and APIs.
Strong web architecture knowledge, including HTTP, DNS, caching strategy, and API delivery paradigms such as REST and GraphQL.
Hands-on experience building and maintaining high-volume distributed services on AWS, including edge delivery and caching via CloudFront or a comparable CDN.
Proven experience leading a legacy platform migration or large-scale standardization effort through completion.
Ability to drive technical decisions beyond your team and explain complex tradeoffs to non-technical stakeholders.
Bachelor’s degree in Computer Science or related technical discipline, or equivalent practical experience.

Technologies

React, TypeScript, server-side rendering
APIs, identity integrations
DNS
Caching strategy
REST, GraphQL
Amazon Web Services (AWS)
CloudFront
Route 53
WAF
Varnish
Edge delivery

Preferred Qualifications

Production configuration of Varnish, HAProxy, or CloudFront, including cache policy design and interactions with experimentation and personalization.
Experience building developer tooling, debugging interfaces, or branch-based deployment models.
Gated AI-assisted development practice with incremental validation and human review of generated changes.
Observability and alerting in Datadog.

Location: Glendale, CA (onsite)

Compensation: USD 155,700 - 208,700 per year

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1mo ago

Software Engineer I

Disney Entertainment and ESPN Product & Technology Glendale, CA

Glendale, CA

1mo ago Closed

$98k - $131k/yr Full time Backend Developer Analytics Automation

This position is no longer accepting applications (closed Sep 19, 2026).

Job Description

Software Engineer I will join the Observability & Insights group to help build telemetry, monitoring, and insights platforms that support Disney’s large-scale streaming services.

Responsibilities

Develop, test, and document features in existing observability codebases across metrics, logs, traces, dashboards, alerting, and telemetry pipelines.
Fix bugs and address technical debt in assigned components with support from senior teammates.
Write clean, readable, and well-tested code aligned to team standards and established observability frameworks.
Learn and apply patterns for high-volume, low-latency telemetry ingestion and storage.
Assist with service instrumentation and validate telemetry quality (metrics, logs, traces) with partner engineering teams.
Build and update dashboards, reports, and visualizations for system health and operational trends.
Tune alerting and reduce noise under guidance from senior engineers and incident response partners.
Participate in code reviews by giving and receiving constructive feedback.
Contribute to technical design discussions for small-to-medium features and document work for maintainability and onboarding.
Work on guided implementation tasks to gain exposure to AWS, Kubernetes, and Infrastructure as Code (IaC).
Shadow on-call rotations and incident response workflows to build operational awareness.
Break down assigned work into clear tasks, ask questions early, and communicate progress and blockers proactively.
Partner across the Observability & Insights group and service engineering teams to deliver incremental improvements.
Participate in team rituals including standups, sprint planning, retrospectives, and knowledge-sharing.
Build foundational skills in reliability engineering concepts such as SLIs, SLOs, post-incident reviews, and blameless culture.

Requirements

Proficiency in at least one backend or systems programming language: Go or Python (coursework, internships, and personal projects count).
Foundational knowledge of software development practices: Git, unit testing, debugging, and working within an existing codebase.
Basic familiarity with cloud computing concepts, with interest in learning AWS and Kubernetes in production environments.
Introductory understanding of observability concepts: metrics, logs, tracing, alerting (or strong motivation to learn quickly).
Ability to communicate clearly, accept feedback, and collaborate effectively in a distributed engineering team.

Technologies

Go, Python, Git
AWS, Kubernetes, Infrastructure as Code (IaC)
metrics, logs, traces, dashboards, alerting, telemetry pipelines
SLIs, SLOs
Grafana, Prometheus, OpenTelemetry, Datadog, New Relic
distributed systems, data pipelines, event-driven architectures
Kafka
CI/CD

Preferred Qualifications

0–2 years of professional software engineering experience, or completion of a relevant internship, co-op, or new-graduate program with demonstrated project work.
Internship, co-op, or project experience related to observability, SRE, DevOps, or platform engineering.
Exposure to observability tools or standards such as Grafana, Prometheus, OpenTelemetry, Datadog, New Relic, or similar.
Experience with distributed systems, data pipelines, or event-driven architectures (academic, internship, or side projects).
Contributions to open source, hackathons, or personal projects showing curiosity and initiative.
Coursework or experience with databases, streaming systems (e.g., Kafka), or CI/CD pipelines.
Familiarity with AI-assisted development workflows and a growth mindset toward modern engineering practices.

Benefits

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.

Role Details

Location: Glendale, CA (onsite)
Compensation: USD 97,500 - 130,700 per yearly
Team: Product Engineering, the unified team responsible for engineering Disney Entertainment & ESPN digital and streaming products and platforms
Group: Observability & Insights
Products supported: Disney+, Hulu, ESPN, ABC, ABC News, and related products

Required Education

Bachelor’s degree in Computer Science, Computer Engineering, Mathematics, Statistics, or a comparable field of study, or equivalent work experience.

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1mo ago

Senior Data Engineer

Software Resources, Inc. Glendale, CA

Glendale, CA

1mo ago Closed

$90 - $93/hr Full time Senior Big Data Data Architecture

This position is no longer accepting applications (closed Sep 18, 2026).

Job Description

Join a hybrid enterprise data engineering team supporting scalable Core Data platform initiatives built on Databricks and Spark.

Responsibilities

Own Core Data platform operations delivering batch and streaming Spark pipelines
Manage Databricks platform governance, including Unity Catalog, ACLS, lineage, and data discovery and privacy tooling
Design, write, test, and deploy data pipelines using PySpark, Scala, SQL, Python, and Kotlin
Gather stakeholder requirements and translate them into scalable data platform solutions
Use Databricks platform tooling to diagnose errors, audit platform activity, and automate updates across pipelines, objects, and integrations
Explain Spark architecture and pipeline behavior to help teams diagnose root causes and recommend solutions
Provide solution architecture across AWS, Databricks, Kubernetes, and Airflow (MWAA), including cross-platform integrations
Build and maintain Kubernetes containers and containerized utilities that support deployed data platform services
Apply networking knowledge to troubleshoot connectivity and integration errors across platform components
Perform platform administration: provision and remove access, assess resource utilization, monitor platform health and cost, and evaluate stakeholder requests
Collaborate with engineers, architects, and product managers to drive Core Data platform success; participate in agile/scrum ceremonies
Maintain documentation of platform changes, standards, and pipeline configurations to support data quality and governance
Develop and maintain scalable data engineering solutions, workflows, and pipeline enhancements
Support cloud-based data platform initiatives and collaborate on system architecture and design
Implement infrastructure automation and deployment standards
Troubleshoot and optimize data processing environments

Requirements

Strong experience with Databricks
Advanced Python development skills
Experience with Terraform and Infrastructure as Code
5+ years of relevant data engineering experience
Ability to participate in architecture and system design discussions
Strong problem-solving and data platform implementation experience

Technologies

Databricks, Python, Terraform, AWS, Kubernetes, Airflow (MWAA)
PySpark, Scala, SQL, Kotlin
Unity Catalog, Apache Spark, Docker
Git-based workflows, CI/CD

Must-Haves

Databricks
Python
Terraform

Nice-to-Haves

Benefits

Medical, dental, and vision coverage
401(k) with company match
Short-term disability
Life insurance with AD&D

Additional Qualifications

5+ years of data engineering experience developing and operating large-scale data pipelines
Deep hands-on experience with Databricks and Apache Spark (batch and streaming), including pipeline development in PySpark and/or Scala
Strong understanding of Spark architecture (executors, stages, partitioning, shuffle) and performance tuning, with ability to explain tradeoffs to technical and non-technical stakeholders
Proficiency with Databricks platform tooling (API, SDK, CLI) for automation, auditing, governance, and operational troubleshooting
Advanced SQL performance tuning capabilities
Hands-on production experience with Airflow (MWAA) for orchestrating data pipelines
Experience managing Databricks governance: ACLS, Unity Catalog, lineage, and access provisioning
Proficiency in Python plus at least one additional language (Scala, Kotlin, or SQL-driven pipeline tooling)
Experience designing and optimizing scalable ETL/ELT pipelines integrating diverse structured and unstructured data sources
AWS-primary experience across compute, storage, networking, and IAM (experience with other cloud providers is transferable)
Proficiency with Docker and Kubernetes for containerized data platform services
Working knowledge of networking concepts for cross-platform integration and connectivity troubleshooting
Familiarity with Snowflake and comparable tooling relative to the Databricks ecosystem
Experience designing and implementing CI/CD and DevOps practices (Git-based workflows)
Experience implementing data quality checks, monitoring, and logging for pipeline reliability
Self-starting problem solver with strong analytical and communication skills; willingness to learn new tooling and trends
Familiar with Scrum and Agile methodologies
Bachelor’s Degree in Computer Science, Information Systems, or related field, or equivalent work experience (Master’s Degree is a plus)
Preferred: Experience with AWS, cloud-based data platform experience, data pipeline optimization and automation expertise
Required: Strong experience with Databricks, advanced Python, Terraform/IaC, 5+ years relevant data engineering experience, ability to participate in architecture and system design discussions, strong problem-solving and data platform implementation experience

Location and Employment Details

Glendale, CA (hybrid)
Duration: 12+ months
Pay rate: USD 90 - 93 per hourly (DOE)
Education: BA/BS
Minimum experience: 5 years

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Developer Jobs in Glendale, CA

Lead Product Software Engineer

Software Engineer I

Senior Data Engineer

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