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BDT Data Engineering Manager

2.00 to 7.00 Years   Hyderabad   11 Aug, 2021
Job LocationHyderabad
EducationNot Mentioned
SalaryNot Disclosed
IndustryIT - Software
Functional AreaGeneral / Other Software
EmploymentTypeFull-time

Job Description

Amazon s eCommerce Foundation (eCF) organization is responsible for the core components that drive the Amazon website and customer experience. Serving millions of customer page views and orders per day, eCF builds for scale.As an organization within eCF, the Business Data Technologies (BDT) group is no exception. We collect petabytes of data from thousands of data sources inside and outside Amazon including the Amazon catalog system, inventory system, customer order system, page views on the website and Alexa systems. We also support Amazon subsidiaries such as IMDB and Audible. We provide interfaces for our internal customers to access and query the data hundreds of thousands of times per day, using Amazon Web Service s (AWS) Redshift, Hive, and Spark. We build scalable solutions that grow with the Amazon business.BDT is growing, and the data processing landscape is shifting. Our data is consumed by thousands of teams across Amazon including Research Scientists, Machine Learning Specialists, Business Analysts and Data Engineers. Amazon.com is seeking an outstanding manager to lead our Data Engineering team of 15 data engineers on the BDT Content team. The BDT Content team manages the core Amazon business data from hundreds of source systems. Amazon.com has culture of data-driven decision-making, and demands business intelligence that is timely, accurate, and actionable. If you join the Amazon.com BDT Content team, your work will have an immediate influence on day-to-day decision making at Amazon.com.As an Amazon.com Data Engineering Manager III you will be working in one of the worlds largest cloud-based data lakes. You should be an experienced manager capable of leading and inspiring a team of excellent data engineers. You should be skilled at helping engineers navigate priorities and communicating clear expectations with customers. You should be knowlegable in the architecture of data warehouse solutions for the Enterprise using multiple platforms (EMR, RDBMS, Columnar, Cloud). You should have experience 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 owners to develop and define key business questions, and to build data sets that answer those questions. Above all you should be passionate about working with huge data sets and someone who loves to bring datasets together to answer business questions and drive change.As a Data Engineering Manager III on Amazon.com s Business Data Technologies team, you will be leading a team of Data Engineers and will play a thought leadership role in our team the team will look to you for advice on data and business issues facing them. You work very efficiently and routinely deliver the right things. You will have a company-wide view of the Data Engineering solutions that you build, and you will consistently think in terms of automating or expanding the results company-wide. This high impact role will have an opportunity to lead a team to help design and build our data infrastructure and work with emerging technologies such as Redshift and associated AWS cloud services while driving business intelligence solutions end-to-end: business requirements, workflow instrumentation, data modeling and ETL. You should be an expert at designing, implementing, and operating stable, scalable, low cost solutions to flow data from production systems into the data lake and into end-user facing applications. The role requires someone who loves data, understands enterprise information systems, has a strong business sense, and can lead a team to put these skills into action., 5+ years of experience as a Data Engineer or in a similar role Experience managing a data or BI team Experience with data modeling, data warehousing, and building ETL pipelines Experience leading and influencing the data strategy of your team or organization Experience in SQL A desire to work in a collaborative, intellectually curious environment. Degree in Computer Science, Engineering, Mathematics, or a related field and 7+ years industry experience Experience managing a technical team Experience Communicating to senior management and customers verbally and in writing Must have two years of experience in the following skill(s): Developing and operating large-scale data structures for business intelligence analytics using: ETL/ELT processes; OLAP technologies; data modeling; SQL; Experience with at least one relational database technology such as Redshift, Oracle, MySQL or MS SQL Experience with at least one massively parallel processing data technology such as Redshift, Teradata, Netezza, Spark or Hadoop based big data solution Industry experience as a Data Engineer or related specialty (e.g., Software Engineer, Business Intelligence Engineer, Data Scientist) with a track record of manipulating, processing, and extracting value from large datasets. Coding proficiency in at least one modern programming language (Python, Ruby, Java, etc) Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets Experience building data products incrementally and integrating and managing datasets from multiple sources Experience leading large-scale data warehousing and analytics projects, including using AWS technologies Redshift, S3, EC2, Data-pipeline and other big data technologies Experience hiring, developing, promoting engineersAmazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success and we make recruiting decisions based on your experience and skills. We welcome applications from all members of society irrespective of age, gender, disability, sexual orientation, race, religion or belief.

Keyskills :
enterprise information systemsbig datasoftware developmentdata structuresdata processingdata modelingsource system analysis

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