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Data Engineer, WFS ACCS Planning

Job ID: 1686112 | ADCI HYD 13 SEZ

DESCRIPTION


DESCRIPTION


Love data as much as we do? Do you enjoy working in an entrepreneurial, fast paced environment, solving complex problems and delivering innovative solutions? Do you like to innovate and simplify? Want to influence at Amazon? We have the career for you.

The ACCS Planning organization owns the end-to-end workforce planning and execution of Amazon's candidate service network. Our forecasting, headcount planning, scheduling, and real-time management solutions are responsible for numerous daily decisions needed to provide efficient and frustration-free support to candidates willing to work for Amazon. We are looking for an experienced professional with excellent analytical skills and strong business acumen to join our Reporting & Analytics team.

Business/Team Introduction


The Amazon Global Workforce Staffing (WFS) Organization is a critical element in bringing on talent to deliver our customer experience around the globe. Our team hires over 700k hourly associates annually and is growing to more than 1M in the next 24 months; WFS is performing an historic and unprecedented task to bring new people to work for Amazon Operations.

The Amazon’s Candidate Connection Services (ACCS) team is one branch of WFS which provides email, chat and phone support to candidates applying for jobs with Amazon. This customer service for candidates removes technical barriers in the hiring process, relieving local HR and Staffing teams from providing Tier 1 candidate support. Candidate Services standardizes candidate messaging and collects actionable data on candidate issues.


JOB RESPONSIBILITIES


As a Data Engineer in Reporting & Analytics team, you will develop new data engineering patterns that leverage new cloud architectures, and will extend or migrate existing data pipelines to the architectures as needed. You will also be assisting with integrating the Redshift platform as our primary processing platform to create the curated Amazon.com data model for the enterprise to leverage. You will be responsible for designing and implementing the complex ETL pipelines in data warehouse platform and other BI solutions to support the rapidly growing and dynamic business demand for data, and use it to deliver the data as service which will have an immediate influence on day-to-day decision making.


You will solve big data warehousing problems on a massive scale. You will apply cloud-based AWS services to solve challenging problems around: big data processing, data warehouse design, and enabling self-service. You will focus on automation and optimization for all areas of DW/ETL maintenance and deployment. You will work closely with the business intelligence engineers, and the software development teams on many non-standard and unique business problems and use creative problem solving to deliver actionable output. The role of a data engineer in Amazon requires excellent technical skills in order to develop systems and tools to process data as well as, but not limited to, the ability to analyze data.

You will succeed in this role if you are an organized self-starter who can learn new technologies quickly and excel in a fast-paced environment. In this position, you will be a key contributor and sparring partner, developing analytics and insights that global executive management teams and business leaders will use to define global strategies and deep dive businesses. You should be highly analytical, resourceful, customer focused, team oriented, and have an ability to work independently under time constraints to meet deadlines. You will be comfortable thinking big and diving deep. A proven track record in taking on end-to-end ownership and successfully delivering results in a fast-paced, dynamic business environment is strongly preferred.


Core responsibilities may include:
· 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


The ideal candidate has an accomplished professional background with demonstrated proficiency in advanced mathematics and/or statistics. They are comfortable creating strategic recommendations in a thoughtful yet concise manner, and obtaining organizational "buy-in" at senior levels. They are well-organized, can manage multiple analyses/projects simultaneously, and are intellectually curious.

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


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.