Mattel

Technology

SeniorDataEngineer

₹25–40L ~AI est. Hyderabad, India FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for mid candidates.

The Brief

“Senior Data Engineer at Mattel. Skills: Data Engineering, Cloud Data Pipelines, BigQuery, Python. Lead development of data integration pipelines. Design and develop data integration pipelines”

Industry & Context.

Technology
Problems you'll solve

Strategic problem-solving

What They're Looking For.

Must Have

Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or related technical field, Minimum 3+ years of hands-on experience in data engineering, Expert-level experience in Google BigQuery, Expert-level experience in Python for data processing, Expert-level experience in SQL for data wrangling, Expert-level experience in DBT for data transformation, Expert-level experience in Airflow / Cloud Composer for workflow orchestration, Proven experience building enterprise-grade ETL/ELT pipelines, Understanding of data quality frameworks, Proficiency in Agile methodologies

Nice to Have

Experience with Ascend.io, Experience with Databricks, Experience with Fivetran, Experience with Dataflow, Experience with data cataloging/governance tools, Experience with CI/CD tools, Experience with Git workflows, Experience with infrastructure automation, Experience with real-time/event-driven data processing, Strategic problem-solving skills, Ability to architect innovative solutions, Ability to adapt quickly to new technologies, Ability to lead adoption across teams, Good experience on Agile Methodologies like Scrum, Kanban, Managing IT backlog

What You'll Do.

Lead development of data integration pipelines

Design and develop data integration pipelines

Ingest data from enterprise systems

Build analytics-ready pipelines

Transform raw data into curated datasets

Implement transformation logic using DBT

and reusable data models

Apply BigQuery best practices

Ensure high performance and scalability

Automate and monitor complex data workflows

Ensure dependable pipeline orchestration

reusable Python and SQL code

Establish robust data quality checks

Establish testing strategies

Partner with architects and Technical leads

Establish best practices

Establish scalable frameworks

Establish reference implementations

Collaborate with cross-functional teams

Understand integration needs

Deliver business-aligned data solutions

Leverage modern ETL platforms

Accelerate development

Improve observability

Improve orchestration

Contribute to technical documentation

Contribute to CI/CD workflows

Contribute to monitoring processes

Drive continuous improvement

Mentor junior engineers

Conduct peer code reviews

Lead technical discussions

How You'll Work.

Team & Collaboration

Cross-functional teams; Architects and Technical leads; Data analysts; BI developers; Product owners

Process & Methodology

Agile methodologies, Scrum, Kanban, IT backlog management

Full Job Description

The Opportunity Mattel is seeking a Senior Data Engineer or Senior ETL Developer, based out of our Technology & Innovation Center in Hyderabad, India, reporting to the IT Director for Enterprise Data and Analytics. This role will lead the design and development of scalable cloud-based data pipelines using tools like BigQuery, Python, SQL, DBT, and Airflow. You will drive detailed designs decisions, ensure data quality, and collaborate with cross-functional teams to deliver trusted, analytics-ready datasets. This role also includes mentoring junior engineers and setting engineering best practices to support Mattel’s enterprise data strategy. What Your Impact Will Be: * Lead the development of scalable, secure, and high-performing data integration pipelines for structured and semi-structured data using Google BigQuery. * 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 and monitor complex data workflows using Airflow/Cloud Composer, ensuring dependable pipeline orchestration and job execution. * 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. * Partner with architects and Technical leads to establish best practices, scalable frameworks, and re

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