Lead Data Engineer

About Mattel and the Enterprise Data & Analytics Team

Mattel is a pioneering global toy company dedicated to fostering innovation and creativity through products that inspire, entertain, and support children's development. Central to our culture is an inclusive environment where every team member feels respected and empowered to contribute their best. Our Enterprise Data & Analytics (ED&A) team, part of the Global Technology Organization, enables data-driven insights across all Mattel business units by designing and managing cloud-native data platforms, scalable pipelines, and curated datasets that power analytics and machine learning initiatives.

Role Overview

The Lead Data Engineer, serving as a Data Architect and Delivery Lead, spearheads the architecture and execution of enterprise-level data solutions. This hybrid position merges technical leadership with accountability over project delivery, encompassing end-to-end design, implementation, and management of cloud-based data platforms and pipelines.

Key Responsibilities

• Integrate diverse enterprise systems including ERP, e-commerce, order management, CRM, and operational platforms into a centralized cloud data warehouse.
• Develop and maintain robust ETL/ELT pipelines for automated data ingestion, transformation, and delivery utilizing modern frameworks.
• Deliver business-ready, curated datasets for self-service analytics and strategic decision-making.
• Ensure data quality, testing, and governance standards are rigorously enforced across data ecosystems.
• Use orchestration tools like Apache Airflow or Google Cloud Composer to reliably schedule and execute data pipelines.
• Collaborate effectively with data analysts, product owners, and BI developers to ensure alignment with business objectives.
• Define scalable, secure, and high-performance cloud-native data platform architectures, emphasizing Google Cloud Platform services such as BigQuery, Cloud Storage, Dataflow, and Cloud Composer.
• Lead design sessions for data models, pipelines, and integration frameworks supporting analytics and BI use cases.
• Coordinate end-to-end delivery of data integration and analytics projects, managing dependencies and timelines across teams.
• Set and uphold architecture standards, design patterns, and best practices within the ED&A organization.
• Create and maintain conceptual, logical, and physical data models, including canonical models to standardize data enterprise-wide.
• Work closely with enterprise architects, application teams, and business units to align data solutions with overarching business goals.
• Mentor engineering teams technically and assist with resolving complex integration and performance challenges.
• Partner with data governance and quality teams to implement consistent lineage, metadata, and quality controls.

Essential Qualifications and Experience

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or equivalent technical discipline.
• Over 12 years of experience in data engineering, solution architecture, or enterprise data management roles.
• Minimum 5 years of leadership in delivering complex cloud data integration or analytics solutions on platforms such as Google Cloud Platform, AWS, or Azure.
• Extensive expertise in data modeling, database architecture (dimensional, normalized, canonical).
• Hands-on experience with cloud-native data services, notably Google Cloud Platform technologies.
• Strong command of ETL/ELT processes, batch and streaming pipelines, and orchestration tools like Airflow or Cloud Composer.
• Proficiency in SQL, Python, and contemporary data engineering frameworks.
• Deep understanding of data governance, security, quality assurance, and metadata management.
• Knowledge of Master Data Management (MDM) and data stewardship concepts.
• Experience managing agile or hybrid delivery teams in cross-functional environments.
• Outstanding communication and stakeholder engagement capabilities.
• Industry experience in retail, media, or consumer products is advantageous.
• Familiarity with machine learning, AI, large language models, or AI-driven data architecture is a plus.

Culture and Values

• Collaboration: Embracing a united team approach with shared goals and mutual respect.
• Innovation: Seeking continuous improvement and valuing fresh ideas to drive impactful change.
• Execution: Commitment to high performance, accountability, and delivering best-in-class results.

Eligibility

Applicants must hold a B.Tech or B.E. degree in any specialization.