Job Summary
6 - 9 years
Machine Supervisor, Data Processing,
Data Entry Machine Operator
Last Date to Apply
24 Jun 2021
Data Engineer
Posted on: 25 Apr 2021
Job Description

Job Description :
Amazons Workplace Health and Safety (WHS) organization is changing the way we think about our workplace, so that we can keep our associates healthy and safe. We have just started scratching the surface in terms of possibilities, and are exploring everything from using devices to monitor and improve health, to linking together data from our buildings and devices to predict safety-related events. Our team is reinventing the way Amazon anticipates, assesses, and manages workplace hazards and risks. So, if creating industry-first products and solutions interests you, then this might be the role for you.

You should be an expert in the architecture of data warehousing solutions, using multiple platforms and tools. In addition, you should have strong analytical skills and excel in the design, creation, management, and business use of large data sets, combining raw information from different sources. Similarly, you will be responsible for designing and implementing scalable extract, transform, and load (ETL) processes to support the rapidly growing and dynamic business demand for data, and use it to deliver the data as a service, which will have an immediate influence on day-to-day business decision making. Moreover, you will create automated alarming and dashboards to monitor data integrity. Finally yet importantly, you should have very good communication skills and ability to adjust communication to different groups of stakeholders, collaborating with architects, Software developers, BI engineers, data scientists, business analysts/managers, to evaluate business needs and objectives in order to set up the best data management environment. Overall, you will be the subject matter expert for the data structures and usage, while striving for efficiency by aligning data systems with business goals.

Basic Qualifications :
Bachelors Degree in Computer Science/Engineering, Informatics, Mathematics, or a related technical discipline
6+ years of industry experience in data Engineering or Software development.
Knowledge of data management fundamentals and data storage principles
At least 6 years of experience working with data pipelines, ETL processes and SQL in a business environment with large-scale, complex datasets; a track record of manipulating, processing and extracting value from large datasets
Fluency in at least one of the programming languages (Python, Ruby, Scala ,Java)
Exposure/Experience in Big data Technologies (hadoop, spark, etc.).
Expertise in the design, creation and management of large datasets/data models
Experience working on building /optimizing logical data model and data pipelines while delivering high data quality solutions that are testable and adhere to SLAs
Experience with AWS services including S3, Redshift, EMR and RDS
Excellent verbal and written communication skills
Ability to work with business owners to define key business requirements and convert to technical specifications
Preferred Qualifications :
Proven success in communicating with users, other technical teams, and senior management to collect requirements, describe data modeling decisions and data engineering strategy
Experience working with other engineers in defining data engineering best practices and leveraging software development life cycle best practices such as agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations.
Knowledge of software engineering best practices across the development life cycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations
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