Ads Central FP&A Finance is seeking a Data Engineer with strong database analytical skills and big data technology experience who is passionate about building scalable next generation tools and data infrastructure to support science and automation.
As a key data solution provider you will be partnering with Finance and Business leaders to design build expand and optimize centralized data solutions. You will be working with massive amount of data and your big data solutions will be supporting our rapidly growing Ads Business and dynamic business demand for data.
In this role you will be able to stretch your technical and analytical skills in developing Data frameworks and large database architecture for building orchestration layers and GenAI solutions for reporting tools and statistical models needed to provide key performance indicators and insights for our highgrowth businesses.
Key job responsibilities Develop data products infrastructure and data pipelines leveraging AWS services (such as Redshift Kinesis EMR Lambda etc. and internal Amazon tools. Improve existing solutions and come up with next generation Ads Finance Data Architecture to improve scale quality timeliness coverage monitoring and security. Develop new data models and end to end data pipelines. Develop a deep understanding of our vast data sources and know exactly how when and which data to use to solve particular business problems.
2 years of data engineering experience Experience with SQL Experience with data modeling warehousing and building ETL pipelines Experience with at least one modern language such as Java Python C or C# including objectoriented design Knowledge of software engineering best practices across the development life cycle including agile methodologies coding standards code reviews source management build processes testing and operations
Experience with AWS technologies like Redshift S3 AWS Glue EMR Kinesis FireHose Lambda and IAM roles and permissions Experience writing and optimizing SQL queries with largescale complex datasets Experience with nonrelational databases / data stores (object storage document or keyvalue stores graph databases columnfamily databases)
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