Experience Inc. Jobs

Description

AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS. Within AWS UC, Amazon Dedicated Cloud (ADC) roles engage with AWS customers who require specialized security solutions for their cloud services.

Annapurna Labs as part of AWS, is looking for Data Engineer to help us develop the semiconductor platform which is based on revolutionary architecture.

As a Data Engineer at Amazon, you will be responsible for designing, developing, and optimizing our data pipelines and infrastructure. You will work closely with cross-functional teams to gather requirements, ensure data quality, and deliver high-quality data solutions. Your expertise in AWS technologies and data engineering will be crucial to our success.

As a member of the System Software team, you’ll join the team in developing infrastructure for data collection, visualizing (dashboards, graphs), alarming and automatic actions. These SW tools are incorporated in all stages of the product development: From design, through validation, manufacturing, testing and monitoring - during production line, and in data centers. You’ll be working with different teams and stake holders across whole AWS.

Key job responsibilities

• Design, develop, and maintain scalable data pipelines to support ongoing data acquisition and processing.

• Collaborate with HW and SW Engineers and other stakeholders to understand data needs and deliver actionable insights.

• Implement data integration and transformation processes using AWS services such as Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, and Lambda.

• Ensure data quality, integrity, and security through rigorous testing and validation.

• Optimize data storage and retrieval processes, to improve system performance and efficiency.

• Develop and manage ETL (Extract, Transform, Load) processes, to integrate data from multiple sources.

• Create and maintain technical documentation for data processes, systems, and workflows.

• Monitor and troubleshoot data pipeline issues, to ensure timely resolution and minimal disruption.

• Stay up-to-date with the latest industry trends and best practices in data engineering and AWS technologies.

• Mentor and guide junior data engineers, providing technical expertise and support.

About the team

Diverse Experiences

AWS values diverse experiences. Even if you do not meet all of the 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 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.

Basic Qualifications

• 8+ years of data engineering experience.

• Familiarity with AWS technologies such as Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions.

• Experience in at least one modern scripting or programming language such as Python, Java, Scala, or NodeJS.

• Experience building data products incrementally and integrating and managing data sets from multiple sources.

• Bachelor's degree in computer science, engineering, analytics, mathematics, statistics, IT, or equivalent.

Preferred Qualifications

• Experience with SQL.

• Experience with non-relational databases/data stores (object storage, document or key-value stores, graph databases, column-family databases).

• Experience building world-class data environments, with high emphasis on data quality and data security.

• Strong problem-solving and analytical skills, with the ability to translate business requirements into technical solutions.