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Lead Software Engineer (Data Platforms)

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Santa Monica, CA

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JOB DETAILS
SALARY
$80–$93 Per Hour
SKILLS
Agile Programming Methodologies, Amazon Web Services (AWS), Application Programming Interface (API), Artificial Intelligence (AI), Automation, Cloud Computing, Code Reviews, Communication Skills, Component Frameworks, Computer Programming, Continuous Deployment/Delivery, Continuous Integration, Cost Control, Cross-Functional, Data Analysis, Data Management, Data Science, Distributed Computing, Ecosystems, Engineering, GraphQL, High Throughput, Java, Leadership, Mentoring, Metadata, Multiplatform/Cross-Platform, Operational Support, Production Systems, Python Programming/Scripting Language, React.js, Reporting Dashboards, Scalable System Development, Software Engineering, Streaming Technology, Team Player, Technical Leadership, Technical Strategy, User Interface/Experience (UI/UX)
LOCATION
Santa Monica, CA
POSTED
30+ days ago
Lead Software Engineer – Data Platform & AI
Pay Range: $80/hour to $93/hour
Overview
We are seeking an experienced Lead Software Engineer to join a high-impact Data Foundation Platform team supporting large-scale data engineering and analytics initiatives. This role focuses on building cloud-based tools, services, and platforms used by data engineers, analysts, and data scientists to process and manage large-scale streaming and web data environments.

The ideal candidate brings deep expertise in software engineering, data infrastructure, metadata governance, and AI-enabled platform development. This position requires strong technical leadership, hands-on engineering capabilities, and experience designing scalable solutions end-to-end.
Key Responsibilities
  • Design, develop, and maintain scalable full-stack data infrastructure and platform services.
  • Build and enhance internal tools supporting metadata management, governance, lifecycle management, and cost management.
  • Architect reusable APIs, shared libraries, and UI component frameworks across data platform ecosystems.
  • Develop user-facing applications and dashboards using modern frontend technologies.
  • Implement cloud-native solutions and automated deployment pipelines within AWS or comparable cloud environments.
  • Collaborate with cross-functional teams including product managers, architects, data scientists, analysts, and engineering teams.
  • Drive technical strategy, system design decisions, and platform scalability initiatives.
  • Mentor engineers through code reviews, architecture reviews, and technical leadership.
  • Support operational excellence, platform reliability, and agile development processes.
  • Contribute to AI-enabled platform capabilities using technologies such as Bedrock, Cortex AI, or similar solutions.
Required Qualifications
  • 12+ years of professional software engineering experience delivering production-scale systems.
  • Strong experience in both software engineering and data engineering environments.
  • Expertise with metadata management and data governance systems.
  • Hands-on experience with AI tools and AI-powered engineering platforms such as Bedrock, Cortex AI, or related technologies.
  • Strong programming skills in at least one core language such as Python, TypeScript, or Java.
  • Experience building and operating distributed systems at scale.
  • Experience with AWS cloud services, CI/CD pipelines, infrastructure-as-code, and deployment automation.
  • Ability to design and implement features end-to-end across backend, frontend, and infrastructure layers.
  • Strong leadership, communication, and collaboration skills.
Preferred Qualifications
  • Experience with internet-scale platforms and high-throughput distributed systems.
  • Hands-on experience with technologies such as:
    • Airflow
    • Spark
    • Databricks
    • Snowflake
    • Delta Lake
    • OpenSearch
    • Neptune
    • GraphQL
    • React
    • TypeScript
  • Experience with data catalog and governance platforms such as Acryl DataHub or Alation.
  • Familiarity with PII governance, compliance, and data lifecycle management.
  • Experience with knowledge graph systems and graph-based architectures.

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