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Apple Analytics Lead ASO Operations Data United States, Texas, Austin 193888935
07.04.2025
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In this role, you will leverage your expertise in data manipulation, ETL processes, and data integration to build a unified data foundation, serving as the single source of truth for ASO Operations business performance and operational metrics. You will collaborate closely with cross-functional teams to design, implement, and maintain robust data pipelines, ensuring the data is clean, scalable, and easily accessible for actionable decision-making. Additionally, you will play a critical role in developing and automating reporting systems that provide stakeholders with timely, accurate insights, enabling data-driven business outcomes and operational improvements.Responsibilities: Define and standardize operational metrics for ASO Operations, ensuring data consistency and alignment across global teams, and building data pipelines that provide reliable, real-time visibility into key performance indicators (KPIs).Develop and implement data strategies to enhance data infrastructure, ensuring the seamless integration of structured and unstructured data sources for comprehensive analysis and decision-making.
- Bachelor’s degree in Computer Science or a technical degree, or 6+ years of relevant professional experience.
- Experience with data engineering tools and technologies, including expertise in SQL (for data querying), Python (for ETL processes and data manipulation), and data pipeline frameworks.
- Experience in designing, building, and maintaining data pipelines for data integration and data warehousing, ensuring high-quality, scalable, and reliable data flow across systems.
- Excellent communication skills, with the ability to collaborate with cross-functional teams and translate complex data processes and systems into clear, actionable insights for technical and non-technical stakeholders.
- Experience with data governance and implementing data quality frameworks, ensuring accurate and consistent data across the organization.
- Familiarity with data modeling, ETL frameworks, and automation tools to manage large-scale data systems efficiently.
- Knowledge and experience with data storage solutions such as relational databases (e.g. MySQL, PostgreSQL), NoSQL databases (e.g. MongoDB, Cassandra), and cloud-based data warehouses (e.g. Snowflake, Amazon Redshift).
- Experience in using data engineering techniques to support workforce or operations planning, including developing data models and pipelines for operational insights and decision-making.
- Strong understanding of business operations, with the ability to leverage advanced analytics to answer complex business management questions and identify root causes, driving informed, data-driven decisions and forecasts.
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