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Data Engineer, AWS Field Exp - BPO - BPX

Amazon Web Services, Inc.
Seattle, Washington, USA
$118.9K a year
Full-time

Amazon Web Services has been the world’s most comprehensive and broadly adopted cloud platform. AWS offers over 100 fully featured services to millions of active customers around the world including the fastest-growing startups, largest enterprises, and leading government agencies to power their infrastructure.

Business Product & Operations (BPO) is a diverse team that supports infrastructure and other foundational initiatives that span and support Sales, Marketing, and Global Services Operations teams within AWS.

We are looking for a hands-on Data Engineer with experience developing and delivering data platform as we build the next iteration of a GenAI based self service platform for Business Insights.

Come join a team at the beginning of a product life cycle and help define the way AWS does business with its key customers.

As a Data Engineer in AWS, you will partner with cross-functional teams, including Business Intelligence Engineers, Analysts, Software Developers, and Product Managers, to develop scalable and maintainable data pipelines on both structured and unstructured data.

The ideal candidate has strong business judgment, a good sense of architectural design, excellent written and documentation skills, and experience with big data technologies (Spark / Hive, Redshift, EMR, and other AWS technologies).

This role involves overseeing existing pipelines as well as developing brand new ones. The operating environment is fast-paced and dynamic, with a strong team-oriented and welcoming culture.

To thrive, you must be detail-oriented, enthusiastic, and flexible, and in return, you will gain tremendous experience with the latest big data technologies and exposure to various use cases to improve process effectiveness, customer experience, and automation.

Key job responsibilities

Design and implement scalable and efficient data pipelines to ingest, transform, and load data from various sources into AWS data stores (e.

g., Amazon S3, Amazon Redshift, Amazon DynamoDB, Amazon Athena)

  • Develop and maintain data ETL (Extract, Transform, Load) processes using AWS services such as AWS Glue, AWS Lambda, AWS EMR, and AWS Step Functions
  • Ensure data integrity, security, and compliance by implementing appropriate data governance policies and access controls
  • Automate data monitoring, alerting, and incident response processes to ensure the reliability and availability of data pipelines
  • Collaborate with data analysts, business intelligence engineers, and business stakeholders to understand data requirements and design solutions to meet their needs
  • Empower technical and non-technical, internal customers to drive their own analytics and reporting by building a self-serve platform and support ad-hoc reporting when needed.
  • Participate in the implementation of data lakes, data warehouses, and other data management solutions on the AWS platform
  • Stay up-to-date with the latest AWS data services, features, and best practices, and recommend improvements to the data architecture
  • Provide technical support and troubleshooting for issues related to data pipelines, data quality, and data processing

About the team

About AWS

Diverse Experiences

AWS 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.

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 & 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.

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.

About Sales, Marketing and Global Services (SMGS)

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.

We are open to hiring candidates to work out of one of the following locations :

Dallas, TX, USA Seattle, WA, USA

BASIC QUALIFICATIONS

  • 3+ years of data engineering experience
  • Experience with SQL
  • Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
  • Experience with data modeling, warehousing and building ETL pipelines
  • Knowledge of distributed systems as it pertains to data storage and computing

PREFERRED QUALIFICATIONS

  • Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
  • Experience with Apache Spark / Elastic Map Reduce
  • Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
  • Experience building / operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
  • Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence
  • Experience working on and delivering end to end projects independently
  • 30+ days ago
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