{"id":76047,"url":"https://alion.io/job/mattel-senior-data-engineer-2","title":"Senior Data Engineer","company":{"id":13477,"name":"Mattel","domain":"mattel.com","url":"https://alion.io/company/mattel-inc","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"SmartRecruiters","truth_index":{"grade":"B","score":75,"open_postings":9,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":25,"computed_at":"2026-11-02T06:13:15Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":20000,"max_usd":43000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":75},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Fivetran","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Kanban","optional":false},{"name":"Python","optional":false},{"name":"Scrum","optional":false},{"name":"SQL","optional":false},{"name":"Apache Kafka","optional":true},{"name":"Collibra","optional":true},{"name":"Git","optional":true}],"status":"live","first_seen_at":"2026-08-08T11:53:21Z","employer_posted_date":"2026-09-29","last_verified_at":"2026-11-02T21:17:09Z","board_verified":true,"closed_at":null,"days_open":86,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":86},"description":"Mattel is a leading global toy and family entertainment company and owner of one of the most iconic brand portfolios in the world. We engage consumers and fans through our franchise brands, including Barbie, Hot Wheels, Fisher-Price, American Girl, Thomas & Friends, UNO, Masters of the Universe, Matchbox, Monster High, MEGA and Polly Pocket, as well as other popular properties that we own or license in partnership with global entertainment companies. Our offerings include toys, content, consumer products, digital and live experiences. Our products are sold in collaboration with the world’s leading retail and ecommerce companies. Since its founding in 1945, Mattel is proud to be a trusted partner in empowering generations to explore the wonder of childhood and reach their full potential.\nMattel’s award-winning workplace culture has been recognized by Forbes, Fast Company, Newsweek, Great Place to Work, TIME, and more.\n 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.\nThis 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.\nWhat Your Impact Will Be:\nLead the development of scalable, secure, and high-performing data integration pipelines for structured and semi-structured data using Google BigQuery.\nDesign 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.\nBuild analytics-ready pipelines that transform raw data into trusted, curated datasets for reporting, dashboards, and advanced analytics.\nImplement transformation logic using DBT to create modular, maintainable, and reusable data models that evolve with business needs.\nApply BigQuery best practices-including partitioning, clustering, and query optimization-to ensure high performance and scalability.\nAutomate and monitor complex data workflows using Airflow/Cloud Composer, ensuring dependable pipeline orchestration and job execution.\nDevelop efficient, reusable Python and SQL code for data ingestion, transformation, validation, and performance tuning across the pipeline lifecycle.\nEstablish robust data quality checks and testing strategies to validate both technical accuracy and alignment with business logic.\nPartner with architects and Technical leads to establish best practices, scalable frameworks, and reference implementations across projects.\nCollaborate with cross-functional teams-including data analysts, BI developers, and product owners-to understand integration needs and deliver impactful, business-aligned data solutions.\nLeverage modern ETL platforms such as Ascend.io, Databricks, Dataflow, or Fivetran to accelerate development and improve observability and orchestration.\nContribute to technical documentation, CI/CD workflows, and monitoring processes to drive transparency, reliability, and continuous improvement across the data engineering ecosystem.\nMentor junior engineers, conduct peer code reviews, and lead technical discussions.\n Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or related technical field.\nMinimum 3+ years of hands-on experience in data engineering with strong expertise in data warehousing, pipeline development, and analytics on cloud platforms.\nExpert-level experience in:Google BigQuery for large-scale data warehousing and analytics.\nPython for data processing, orchestration, and scripting.\nSQL for data wrangling, transformation, and query optimization.\nDBT for developing modular and maintainable data transformation layers.\n Airflow / Cloud Composer for workflow orchestration and scheduling.\n\nProven experience building enterprise-grade ETL/ELT pipelines and scalable data architectures.\nStrong understanding of data quality frameworks, validation techniques, and governance processes.\nProficiency in Agile methodologies (Scrum/Kanban) and managing IT backlogs in a collaborative, iterative environment.\nPreferred experience with:Tools like Ascend.io, Databricks, Fivetran, or Dataflow.\nData cataloging/governance tools (e.g., Collibra).\nCI/CD tools, Git workflows, and infrastructure automation.\nReal-time/event-driven data processing using Pub/Sub, Kafka, or similar platforms.\n\nStrategic problem-solving skills and ability to architect innovative solutions.\nAbility to adapt quickly to new technologies and lead adoption across teams.\nExcellent communication skills and ability to influence cross-functional teams.\nGood experience on Agile Methodologies like Scrum, Kanban, and managing IT backlog.\nBe a “go-to” expert for data technologies and 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