Data Engineer ( Level 5)

Job description

DESCRIPTION

Amazon IN Advertising team is looking for a passionate data engineer to help build and test customer-facing and operator-facing, that both delight and help our customers and operators to optimize their costs by shipping with Amazon. You will work with scientists and engineers on a variety of online and offline machine learning use cases.

As a Data Engineer, you should be an expert in the architecture of DW solutions for the Enterprise using multiple platforms. You should excel in the design, creation, management, and business use of extremely large datasets. You should have excellent business and communication skills to be able to work with business analysts and engineers to determine how best to design the data warehouse for reporting and analytics. You will be responsible for designing and implementing scalable ETL processes in the data warehouse platform 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 should have the ability to develop and tune SQL to provide optimized solutions to the business.

Do you have the technical chops to build BI solutions that process billions of rows a day using AWS technologies? Do you want to create next-generation tools for intuitive data access? Do you wake up in the middle of the night with new ideas that will benefit your customers? Are you persistent in bringing your ideas to fruition?

First things first, you know SQL and data modelling like the back of your hand. You also need to know Big Data and MPP systems. You have a history of coming up with innovative solutions to complex technical problems. You are a quick and willing learner of new technologies and have examples to prove your aptitude. You are not tool-centric; you determine what technology works best for the problem at hand and apply it accordingly. You can explain complex concepts to your non-technical customers in simple terms.

PREFERRED QUALIFICATIONS

· 5+ years of experience as a Data Engineer, BI Engineer, Business/Financial Analyst 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 for serverless ETL)
· Demonstrated strength in data modeling, ETL development, and data warehousing
· 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

Desired profile

BASIC QUALIFICATIONS

· Bachelor's degree in computer science, engineering, mathematics, or a related technical discipline
· 4+ years of industry experience in software development, data engineering, business intelligence, data science, or related field with a track record of manipulating, processing, and extracting value from large datasets
· Experience writing high quality, maintainable SQL on large datasets.
· 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
· Knowledge of data management fundamentals and data storage principles
· Knowledge of distributed systems as it pertains to data storage and computing
· 3+ years of Data Engineering experience.
· Excellent verbal and written communication skills
· Ability to work with business owners to define key business requirements and convert to technical specifications