Company Overview: Our client is at the forefront of revolutionizing the fashion industry by integrating cutting-edge AI technology with user-friendly interfaces to provide personalized fashion experiences. Their mission is to empower users to discover and shop fashion that aligns with their unique style. They are looking for a talented Back-End Engineer who specializes in data organization to join their dynamic team and help them manage and streamline their vast product catalogs and content from various sources. Job Description: They are seeking an experienced Back-End Engineer with a specialization in data organization to join their development team at Aesthetic. The ideal candidate will have a strong background in handling data feeds and pipelines, and a passion for creating efficient, scalable solutions. As a Back-End Engineer, you will be responsible for designing, building, and maintaining the infrastructure that ingests, processes, and organizes large volumes of product data and content. Key Responsibilities: Design, develop, and maintain robust data pipelines to ingest and process product catalogs and content from various sources. Implement and optimize ETL (Extract, Transform, Load) processes to ensure data is clean, accurate, and accessible. Develop and maintain databases and data storage solutions to efficiently organize and retrieve large datasets. Collaborate with front-end developers, data scientists, and other stakeholders to ensure seamless integration and utilization of data. Monitor and troubleshoot data pipelines and workflows to ensure reliability and performance. Implement data validation and quality assurance processes to maintain data integrity. Stay up-to-date with emerging technologies and best practices in data engineering and apply them to improve our systems. Qualifications: Bachelor's degree in Computer Science, Information Technology, or a related field, or equivalent experience. Proven work experience as a Back-End Engineer or Data Engineer. Strong proficiency in programming languages such as Python. Experience with data processing frameworks such as FIvetran, Stitch, Talend. Proficiency in SQL and experience with relational databases specifically MySQL and PostgreSQL. Familiarity with NoSQL databases such as MongoDB. Experience with ETL tools and processes. Strong problem-solving skills and attention to detail. Excellent communication and teamwork skills. Ability to manage multiple tasks and projects simultaneously. Preferred Qualifications: Experience with cloud platforms such as AWS and Google Cloud. Knowledge of data warehousing solutions such as Amazon Redshift, Google BigQuery, or Snowflake. Familiarity with containerization and orchestration tools such as Docker and Kubernetes. Understanding of data governance and compliance best practices. Practical Responsibilities While their application is unique, many of the interfaces, components, and design systems will resemble those found in platforms like Instagram, Spotify, Facebook, or TikTok, including user interactions, search, filtering, recommendations, and communication. They are looking for someone who can provide practical examples of their work on these types of features and clearly demonstrate their development from initial requests to final working implementation. Below are just a small set of the types of things you'd be developing and solving for: Database Management Design and maintain relational databases using SQL (MySQL, PostgreSQL) and NoSQL databases (MongoDB). Develop and optimize complex queries and database schema updates. API Development Create and maintain back-end API endpoints for front-end interactions, including media processing, product search recommendations, and integrations with vector databases for image-based matching (experience with vector databases is a plus). Media Processing Handle the storage, optimization, resizing, and scaling of large volumes of images and videos within cloud platforms (AWS, GCP). Data Pipeline Integration Design and manage data pipelines to ingest and process diverse data formats (FTP, APIs, CSV, TSV, JSON). Integrate data from sources like Shopify and BigCommerce, and build endpoints for external developer access. ETL Processes Implement and optimize ETL (Extract, Transform, Load) processes for data cleaning, validation, and integration. Ensure data integrity across multiple third-party feeds and platforms. Data Schema and Migrations Design and update database schemas and migrations to support features such as profile editing, collections, commenting, notifications, chat bots, and search/filtering. Product Search API Develop APIs to aggregate and format product data for front-end rendering and filtering. Affiliate and Marketing Tracking Manage analytics tracking for performance marketing, including impressions, clicks, and conversion data ingestion from third-party systems. Stripe Integration Implement and manage Stripe integration for handling payouts to a large number of creator and influencer partners. Data Analytics Reporting Develop custom data analytics reporting tools and dashboards using platforms like Google Data Studio "Looker" to provide insights and support decision-making.
