Description Overview Amazon.com strives to be Earth's most customer-centric company where people can find and discover virtually anything they want to buy online. By giving customers more of what they want - low prices, vast selection, and convenience - Amazon.com continues to grow and evolve as a world-class e-commerce platform. Amazon's evolution from Web site to e-commerce partner to development platform is driven by the spirit of innovation that is part of the company's DNA. The world's brightest technology minds come to Amazon.com to research and develop technology that improves the lives of shoppers and sellers around the world. Job Description Are you passionate about designing and building robust data pipelines that power data-driven insights for business impact? Do you thrive in an environment where you can leverage the latest data engineering technologies to tackle complex challenges? We are seeking a talented Data Engineer to join our Talent Acquisition (TA) team and help drive our data-powered analytical revolution. In this role, you will be responsible for designing and developing highly efficient data pipelines that seamlessly extract, transform, and load data from a diverse array of sources. You will work closely with our Business Intelligence, Data Science, and Product teams to uncover new data sources, optimize data delivery, and deliver high- quality, actionable insights to support our TA initiatives. Responsibilities: Design and develop highly efficient data pipelines that seamlessly extract, transform, and load data from a diverse array of sources using SQL, Python, and AWS big data technologies. Oversee and continuously enhance production operations, optimizing data delivery, redesigning infrastructure for greater scalability, managing code deployments, addressing bugs, and coordinating overall release management. Establish and uphold best practices for the design, development, and support of data integration solutions, including comprehensive documentation. Collaborate closely with Product teams, Data Scientists, Software Developers, and Business Intelligence Engineers to uncover new data sources and deliver high-impact insights. Demonstrate proficiency in reading, writing, and debugging data processing and orchestration code in Python/Scala, adhering to the highest coding standards (e.g., version control, code review, etc.). Basic qualifications: Bachelor's degree in Computer Science, Data Science, Engineering, or a related technical field Minimum 3-5 years of experience in data engineering or a similar role Hands-on experience designing, developing, and maintaining data pipelines and data integration solutions Proficient in SQL, Python, and AWS big data technologies (e.g., EMR, Glue, Athena, Redshift) Strong understanding of data architecture, data modeling, and ETL/ELT processes Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets Experience with version control systems (e.g., Git) and code review best practices Exposure to building scalable and fault-tolerant data processing systems Preferred Qualifications: Advanced experience with cloud-native data engineering tools and platforms (e.g., Databricks, Snowflake, Kafka, Kinesis) Proficiency in writing high-performance, scalable, and maintainable code (e.g., using design patterns, unit testing, refactoring) Familiarity with data streaming and real-time data processing frameworks Exposure to machine learning and artificial intelligence techniques for data- driven insights Proven track record of leading data engineering projects from inception to delivery Experience in mentoring and training junior data engineers Demonstrated ability to identify and implement process improvements, optimize data pipelines, and enhance overall data infrastructure Passion for staying up-to-date with the latest data engineering trends and technologies, and a willingness to explore new tools and approaches Basic Qualifications - 3+ years of data engineering experience - Experience with data modeling, warehousing and building ETL pipelines - Experience with SQL Preferred Qualifications - Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions - Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)