Data Engineering | Amazon | Amazon Careers | Job Alert | Latest Jobs 2021
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You will build new data engineering patterns that utilise new cloud architectures as a Data Engineer in the Reporting & Analytics team, and you will expand or migrate existing data pipelines to the architectures as appropriate. You’ll also help with integrating the Redshift platform as our primary processing platform so that the enterprise may use the curated Amazon.com data model.
You’ll be in charge of designing and implementing complex ETL pipelines in data warehouse platforms and other BI solutions to support the rapidly growing and dynamic business demand for data, and then using that data to deliver data as a service that will have an immediate impact on day-to-day decision making.
On a vast scale, you’ll solve big data warehousing difficulties. You’ll leverage cloud-based AWS services to solve problems including large data processing, data warehouse design, and self-service enablement. You’ll be responsible for all aspects of DW/ETL maintenance and deployment, with a focus on automation and optimization. You’ll collaborate directly with business intelligence engineers and software development teams on a variety of non-standard and unusual business problems, using creative problem-solving to produce meaningful results.
A data engineer’s job at Amazon necessitates great technical abilities in order to design data processing systems and tools, as well as the capacity to evaluate data.
You’ll be successful in this role if you’re a well-organized self-starter who can rapidly pick up new technologies and thrive in a fast-paced atmosphere. You will be a significant contributor and sparring partner in this position, providing analytics and insights that will be used by global executive management teams and business leaders to establish global strategies and deep dive businesses.
You should be highly analytical, resourceful, customer-focused, team-oriented, and able to work independently to fulfil deadlines under time restrictions. You’ll feel confident in your ability to think large and dive deep. It is strongly desirable if you have a track record of successfully taking on end-to-end ownership and producing results in a fast-paced, dynamic company environment.
- Design, implement and support an analytical data infrastructure providing ad-hoc access to large datasets and computing power.
- Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL and AWS big data technologies.
- Must possess strong verbal and written communication skills, be self-driven, and deliver high quality results in a fast-paced environment.
- Enjoy working closely within and outside the teams.
- Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers.
- Explore and learn the latest AWS technologies to provide new capabilities and increase efficiency
- BASIC QUALIFICATIONS
- Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related technical discipline.
- Industry experience in Data Engineering, BI Engineer, or related field.
- Track record of data management fundamentals and data storage principles.
- Hands-on experience and advanced knowledge of SQL, DynamoDB etc.
- Demonstrated strength in data modeling, ETL development, and data warehousing Knowledge of distributed systems as it pertains to data storage and computing.
- PREFERRED QUALIFICATIONS
- 3+ years of experience as a Data Engineer, BI Engineer, or Systems Analyst in a company with large, complex data sources.
- Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
- Experience working with AWS big data technologies (EMR, Redshift, S3, Glue, Kinesis and Lambda)
- Proven success in communicating with users, other technical teams, and senior management to collect requirements, describe data modeling decisions and data engineering strategy
- Experience providing technical leadership and mentoring other engineers for best practices on data engineering
- Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations.
- Excellent interpersonal, written and oral communication skills
- Natural curiosity and desire to learn
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