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Key job responsibilities
- Conduct data discovery and profiling for various data sources, including Page0, entitlement models, and propensity models.- Develop and maintain efficient data ingestion processes, ensuring timely and accurate data availability.
- Design and develop effective data models and schemas for Page0 data, entitlement model data, propensity model data, and other relevant data sources.- Implement and maintain a centralized data warehouse architecture, ensuring scalability, performance, and data integrity.
- Collaborate with stakeholders to understand data requirements and translate them into optimized data structures and models.
- Establish and enforce data governance policies and procedures to maintain data quality, consistency, and integrity across the organization.- Implement data quality controls, monitoring, and reporting mechanisms to ensure data accuracy and reliability.
- Continuously monitor data quality, identify issues, and implement remediation measures as needed.- Design and implement centralized data integration pipelines to consolidate data from various sources into a unified data platform.
- Ensure seamless data integration and interoperability between different systems, applications, and processes.
- Integrate propensity models with downstream systems and processes, facilitating data-driven decision-making.
- Implement robust data security measures, including access controls, authentication, and authorization mechanisms, to protect sensitive data.- Continuously monitor data flows and optimize performance by identifying bottlenecks and implementing efficient solutions.
- Develop and implement data retention and archiving policies to manage data growth and storage requirements.- Establish data disaster recovery and business continuity plans to ensure data availability and resilience.
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.Why AWSWork/Life BalanceInclusive Team CultureMentorship and Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
- 2+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with at least one modern language such as Java, Python, C++, or C# including object-oriented design
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