About
Develop and maintain automated ETL pipelines (with monitoring) using scripting languages such as Python, Spark, SQL and AWS services like S3, Glue, Lambda, SNS, SQS, KMS. Establish and support the reporting and analytics infrastructure for internal business users. Create and implement data security and permission solutions for enterprise-scale data warehouse and data lake deployments, including encryption and access control with logging. Design data objects for business analytics using data modeling techniques. Optimize data warehouse and data lake tables, employing best practices for data definition language (DDL), partitioning, compression, and parallelization. Maintain data warehouse and data lake metadata, data catalogs, and user documentation for internal business users. Collaborate with internal business teams and software development groups to gather and document requirements for data publishing and consumption via the data warehouse, data lake, and analytics solutions. Imagine a day in your role where you're not merely managing data but crafting intelligent systems that convey compelling narratives. Your daily activities will include exploring innovative data transformation techniques, developing automated reporting solutions, collaborating with cross-functional teams to tackle complex analytical challenges, and researching emerging technologies that could transform our data strategy. About Us:
At Amazon Web Services (AWS), we are the world’s most extensive and widely adopted cloud platform. Our pioneering efforts in cloud computing set the stage for continued innovation, making AWS the trusted choice for everything from startups to global enterprises. Diverse Experiences:
AWS deeply values diverse experiences. Even if you don't meet every preferred qualification mentioned, we encourage you to apply. If your career is just beginning, hasn’t followed a traditional path, or includes alternative experiences, don’t let that deter you from applying. Work/Life Balance:
We prioritize work-life harmony. Achieving success at work should complement, not compromise, your personal life. That’s why we strive for flexible working conditions. Inclusive Culture:
AWS fosters curiosity and connection, organizing employee-led and company-sponsored affinity groups that promote inclusion and empower everyone to take pride in their uniqueness, fostering stronger, collaborative teams. Our ongoing innovation is driven by the diverse ideas, perspectives, and passions our teams contribute. BASIC QUALIFICATIONS:
3+ years of data engineering experience. Experience with data modeling, warehousing, and building ETL pipelines. Knowledge of professional software engineering and best practices throughout the software development lifecycle, including coding standards, architectures, code reviews, source control, continuous deployment, testing, and operational excellence. PREFERRED QUALIFICATIONS:
Experience with non-relational databases/data stores (object storage, document or key-value stores, graph databases, column-family databases). Familiarity with AWS technologies like Redshift, S3, Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need workplace accommodation or adjustment during the application and hiring process, please seek assistance. The base salary range for this position in Seattle is $132,100.00 to $178,800.00 USD annually, along with additional compensation and comprehensive benefits including health insurance, 401(k) matching, paid time off, and parental leave.
Languages
- English
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