Job Information
Amazon Data Engineer, WWPS Data Products and Engineering in Arlington, Virginia
Description
The Data Products and Engineering (DataEng) Team within the AWS World Wide Public Sector (WWPS) Engineering organization is a team of experts in the fields of data engineering, research science, and applied science. We develop data products for internal teams and ML/AI based prototypes for public sector customers. Internally, we work together to define best practices and areas for advancement in our respective fields. We provide design reviews to scale our impact across multiple teams. We share our knowledge more broadly via published research, AWS blog posts, and documentation for AWS-internal use. We are a new formed team looking for a Data Engineer with a passion for working with customers, problem solving, and mastering the latest AWS technologies to evolve our data platform for use across the WWPS organization.
Key job responsibilities
The DataEng team has recently launched a new data platform to support software and systems development teams that build internal first-party solutions for the WWPS Business. As a data engineer joining our team, you will be part of a team that owns this platform.
You will define advancements to the architecture.
You will review and provide guidance on when to leverage the latest AWS technologies.
You will work directly with the software engineering teams to optimize the ingestion of current and future data sets.
You will evolve the data platform to support new applications and use cases; such as analytics, modeling for Gen AI features, and reporting.
You will define and manage an ETL process into a central AWS data warehouse; making the appropriate data sets available across WWPS.
You will set a high bar for availability and resilience in production.
A day in the life
As a specialist in data engineering, you wear many hats to support the organization.
You work hands-on with SDEs to structure and manage data coming into the data platform.
You focus on operational excellence, assuring the appropriate monitors are in place to assure the success of ETL jobs, data hygiene, and general availability of the data platform.
You carve out time to stay up to speed on relevant AWS technologies (S3, DynamoDB, Redshift, Glue, Kinesis, to name a few), data management best practices, and AI with an eye towards understand what will be needed next.
You work with our team of data engineers, applied scientists, and research scientists to advise on how structure data for Gen AI prototypes for public sector customers.
About the team
The mission of the Data Products and Engineering team is to define and build solutions that empower AWS World Wide Public Sector teams and customers to increase business impact through deeper understanding and use of their data. We have team members in multiple Amazon hubs across the US East coast that work with teams from around the world. Though we are geographically spread out, we find creative ways maintain a welcoming and social team. We are a team that biases heavily towards learn Learn and Be Curious. We enjoy diving deep and sharing our findings across the team.
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 AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
Mentorship 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.
AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services.
Basic Qualifications
3+ years of data engineering experience
Experience with data modeling, warehousing and building ETL pipelines
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)
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.
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