Data Engineer - EAI job opportunity at Mattel, Inc.

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Date2026-05-13T10:51:18.853Z bot
Mattel, Inc Data Engineer - EAI
Experience: General
Pattern: Full-time
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loacation 1804, 18th Floor, Gowra Palladium, Hyderabad, India
loacation 1804, 18th Flo..........India
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Job DescriptionThe Opportunity: Mattel is seeking a Data Engineer or ETL Developer, based out of our Technology & Innovation Center in Hyderabad, India, reporting to the IT Director for Enterprise Data and Analytics. The person in this role will be responsible for designing, developing, and maintaining scalable data integration and analytics pipelines to support enterprise reporting and data-driven decision-making. This role requires close collaboration with cross-functional teams to integrate data from various source systems into a centralized, cloud-based data warehouse—primarily leveraging tools such as Google Big Query, Python, SQL, DBT, and Cloud Composer (Airflow). The Data Engineer will also be responsible for implementing data quality checks, managing orchestration workflows, and delivering business-ready datasets aligned with Mattel’s enterprise data strategy. What Your Impact Will Be:Design and develop scalable data integration pipelines to ingest structured and semi-structured data from enterprise systems (e.g., ERP, CRM, E-commerce, Order Management) into a centralized cloud data warehouse using Google BigQuery.Build analytics-ready pipelines that transform raw data into trusted, curated datasets for reporting, dashboards, and advanced analytics.Implement transformation logic using DBT to create modular, maintainable, and reusable data models that evolve with business needs.Apply BigQuery best practices—including partitioning, clustering, and query optimization—to ensure high performance and scalability.Automate data workflows using Cloud Composer (Airflow), ensuring reliable execution, task dependency management, and timely data delivery.Develop efficient, reusable Python and SQL code for data ingestion, transformation, validation, and performance tuning across the pipeline lifecycle.Establish robust data quality checks and testing strategies to validate both technical accuracy and alignment with business logic.Collaborate with cross-functional teams—including data analysts, BI developers, and product owners—to understand integration needs and deliver impactful, business-aligned data solutions.Leverage modern ETL platforms such as Ascend.io, Databricks, Dataflow, or Fivetran to accelerate development and improve observability and orchestration.Contribute to technical documentation, CI/CD workflows, and monitoring processes to drive transparency, reliability, and continuous improvement across the data engineering ecosystem.

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