Data Engineer II, Shopbop

Key Skills

Ruby on Rails, Java Programming, Oracle, Python Programming, SQL, AWS, Big Data Technology, Business Intelligence, Tableau, Apache Hive, Amazon Athena, PostgreSQL, Amazon RedShift, Amazon EMR, Amazon Elastic Compute Cloud-EC2, SPARK Programming, Lambda, Amazon Simple Storage Service (S3), Data Engineering, IBM Cognos, Large scale data processing, Data pipelines, QuickSight, Large data sets, Terabyte scale datasets, Data Warehousing

Job Description

Shopbop | East Dane is looking for a Data Engineer to help us to grow our business and support our mission to be the daily destination for fashion worldwide. You will be part of an innovative team of data engineers who are continuously raising the bar in building and maintaining best-in-class data infrastructures for an enterprise level data warehouse, built using the latest Amazon AWS technologies and services. Our engineers learn from and contribute to one of the strongest technology groups in the world, with access to the world’s best cloud computing infrastructure.

About Shopbop | East Dane

Since its launch in 2000 as a modestly sized online boutique specializing in hard-to-find denim lines, Shopbop has grown to become one of the leading fashion retailers in the world. Curated with a chic, modern woman in mind, Shopbop offers a comprehensive collection of designer apparel and accessories to suit every style and occasion.

Called the editors of what's cool by Daily Candy, and recognized by The Wall Street Journal as having the best customer service, we are committed to staying ahead of the curve and providing a personalized shopping experience continue to be driving forces behind the company's success. A champion of new design talent and a pioneer in the magazine-meets-boutique approach to online shopping, Shopbop showcases its fashion-forward point of view in editorial lookbook features and receives frequent mention in Vogue, Harper's Bazaar, and Elle. Shopbop's Exclusives section features limited-edition pieces from top designers available only at Shopbop. We are not resting on our laurels. We have the pleasure of delighting some of the world’s most passionate clothing and apparel shoppers worldwide.

Key job responsibilities

• Design and build infrastructure required for data extraction and transformation leveraging AWS ‘big data’ technologies
• Explore and learn the latest AWS technologies to provide new capabilities and increase efficiency
• Work with complex structured and unstructured data (batch and streaming)
• Implementing best practices for software development and documentation, ensuring designs meet requirements, and delivering high quality work on tight schedules
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, redesigning infrastructure for greater scalability, etc
• Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers

BASIC QUALIFICATIONS

• A desire to work in a collaborative, intellectually curious environment
• Degree in Computer Science, Engineering, Mathematics, or a related field with 2+ years of industry experience
• Demonstrated strength in data modeling, ETL development, and data warehousing
• Data Warehousing Experience preferably with Oracle, Redshift, PostgreSQL
• Query performance tuning skills, proficcient in SQL
• Experience using big data technologies such as Spark, Hive, EMR
• Coding proficiency in at least one modern programming language (Python, Ruby, Java, etc.)
• Experience working in a cloud infrastructure environment and using various AWS technologies - Data-pipeline, Redshift, Athena, S3, EC2
• Knowledge and direct experience using data integration tools. (e.g.Informatica, Talend)

PREFERRED QUALIFICATIONS

• Master's degree in Engineering or Math/Statistics/ or related discipline
• 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
• 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 using AWS technologies – Redshift, Data-pipeline, Lambda, Athena, S3, EC2 and other big data technologies
• Knowledge and direct experience using business intelligence reporting tools. (e.g.Cognos, Tableau, QuickSight etc.)
• Proven success in communicating with users, other technical teams, and senior management to collect requirements, describe data modeling decisions and data engineering strategy