Job Details

Job Overview - Senior Data Engineer

Location: Burbank, CA (Hybrid - 3 days onsite)
Pay Rate: $80-$88/hour
Contract End Date: 12/31/2026

Role Overview

This role supports a large-scale finance and business transformation initiative, focused on modernizing how finance, business, and technology teams collaborate. The organization is moving toward a lean-agile, product-oriented delivery model, built around small, empowered product pods (PODs) that own outcomes end-to-end.

Each pod is cross-functional, bringing together engineers, product owners, designers, data architects, and domain experts to deliver scalable, intelligent solutions. Teams prioritize collaboration over handoffs, iterative delivery over heavy documentation, and shared accountability for outcomes. A strong emphasis is placed on reusability, automation, platform-first design, and long-term maintainability.

The Senior Data Engineer is a hands-on contributor within the Platform Pod, responsible for building and maintaining high-quality, reusable data pipelines and services. This role partners closely with data architects, cloud architects, and application teams to deliver governed, analytics- and AI/ML-ready data products.

Key Responsibilities

• Design, build, and maintain scalable batch and streaming data pipelines using cloud-native services and modern orchestration frameworks
• Partner with architects to translate canonical and semantic data models into production-ready physical implementations
• Enable analytics, BI, and AI/ML workflows by delivering clean, well-structured, and reliable data
• Embed data quality checks, validation, lineage, and anomaly detection directly into pipelines
• Contribute to enterprise data governance efforts, including schema alignment, cataloging, access controls, and metadata standards
• Mentor junior engineers and promote best practices in pipeline design, coding standards, and reusable platform services
• Actively participate in agile pod ceremonies, architecture syncs, and continuous improvement initiatives

Required Qualifications

• 7+ years of experience in data engineering
• Strong hands-on experience with cloud-based data services and orchestration tools
• Advanced proficiency in SQL, Python, PySpark, and data transformation scripting
• Experience with modern data platforms such as Snowflake, Databricks, Redshift, or Informatica
• Proven ability to design and optimize pipelines for both batch and streaming workloads

Preferred Qualifications

• Familiarity with data governance practices, including lineage, validation, and data cataloging
• Strong collaboration and mentoring skills with the ability to influence across teams and domains

Education / Certifications

• No formal education or certifications required

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