Data Engineer II

Bachelors or Master’s Degree in Computer Science/Engineering, Information Technology with at least 6+ years of experience in Data Engineering Applications with following skills:

• Excellent knowledge and experience of designing and developing data engineering systems from grounds up and maintaining/supporting existing systems.
• Excellent knowledge of ETL tools and various data processing techniques
• Excellent knowledge of data warehousing and big data design and concepts
• Experience in dealing with large and complex data sets and performance tuning
• Experience in designing data models that supports structures and unstructured data
• Experience in gathering requirements and formulating business metrics for reporting
• Strong verbal/written communication & presentation skills, including an ability to effectively communicate with business: technical and technical teams.
• Ability to deal with ambiguities and competing priorities.

AWS Databases, Analytics and AI/ML Products and Services is one of the largest and fast growing business unit within AWS. We are working to rebuild and revolutionize data engineering and business intelligence systems within database, analytics and AI/ML organization to support fast growing business needs.

We are looking for experienced, self-driven Data Engineer. In this role, you will be building complex data engineering and business intelligence applications using AWS big data stack. You should have deep expertise and passion in working with large data sets, data visualization, building complex data processes, performance tuning, bringing data from disparate data stores and programmatically identifying patterns. You should have excellent business acumen and communication skills to be able to work with business owners to develop and define key business questions and requirements. You will provide guidance and support for other engineers with industry best practices and direction. Amazon Web Services (AWS) has culture of data-driven decision-making, and demands timely, accurate, and actionable business insights.

Key Responsibilities:

• Design, implement, and support data warehouse / data lake infrastructure using AWS big data stack, Python, Redshift, Quicksight, Glue/lake formation, EMR/Spark/Scala, Athena etc.
• Develop and manage ETLs to source data from various commercial, sales and operational systems and create unified data model for analytics and reporting
• Use business intelligence and visualization software (e.g., Quicksight.) to develop dashboards those are used by senior leadership.
• Empower technical and non-technical, internal customers to drive their own analytics and reporting (self-serve reporting) and support ad-hoc reporting when needed.
• Develop deep understanding of vast data sources and know exactly how, when, and which data to use to solve particular business problems.
• Work with Product Managers, Finance, Service Engineering Teams and Sales Teams on day to day basis to support their new analytics requirements.
• Manage numerous requests concurrently and strategically, prioritizing when necessary
• Partner/collaborate across teams/roles to deliver results.
• Mentor other engineers, influence positively team culture, and help grow the team.
• Prior experience in AWS stack including Glue Crawler, Glue Catalog, Glue Pipelines, Lake Formation, Redshift, Quicksight, EMR/Hive, Spark, Scala,
• Prior experience in programming using Python
• Experience with AWS as cloud
• AWS certification will be plus.
• Any knowledge/skill on Data Science, AI/ML will be plus

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities
who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and we host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.