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Data Architect, Data Lake, Professional Services
hace 2 meses
At Amazon Web Services (AWS), we’re hiring highly technical data architects to collaborate with our customers and partners on key engagements. Our consultants will develop, deliver and implement data analytics projects that help our customers leverage their data to develop business insights. These professional services engagements will focus on customer solutions such as Data and Business intelligence, machine Learning and batch/real-time data processing.
Responsibilities include:
- Delivery - Help the customer to define and implement data architectures (Data Lake, Lake House, Data Mesh, etc). Engagements include short on-site projects proving the use of AWS Data services to support new distributed computing solutions that often span private cloud and public cloud services.
- Solutions - Deliver on-site technical assessments with partners and customers. This includes participating in pre-sales visits, understanding customer requirements, creating packaged Data & Analytics service offerings.
- Innovate- Engaging with the customer’s business and technology stakeholders to create a compelling vision of a data-driven enterprise in their environment. Create new artifacts that promotes code reuse.
- Expertise - Collaborate with AWS field sales, pre-sales, training and support teams to help partners and customers learn and use AWS services such as Athena, Glue, Lambda, S3, DynamoDB, Amazon EMR and Amazon Redshift.
- Since this is a customer facing role, you might be required to travel to client locations and deliver professional services when needed, up to 50%.
About 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 we strive for flexibility as part of our working 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.
BASIC QUALIFICATIONS- Experience implementing AWS services in a variety of distributed computing environments
- 3+ years of experience of Data Lake/Hadoop platform implementation
- 2+ years of hands-on experience in implementation and performance tuning Hadoop/Spark implementations.
- Experience Apache Hadoop and the Hadoop ecosystem
- Experience with one or more relevant tools (Sqoop, Flume, Kafka, Oozie, Hue, Zookeeper, HCatalog, Solr, Avro)
PREFERRED QUALIFICATIONS- Hands on experience leading large-scale full-cycle MPP enterprise data warehousing (EDW) and analytics projects (including migrations to Amazon Redshift).
- At least one of the AWS Associate level certifications or higher.
- Ability to lead effectively across organizations and partners.
