LTK · 1 week ago

Staff Software Engineer

United States

Full-time

Remote

Senior Level

7+ years exp

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Brand MarketingFashion

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Responsibilities

Lead the building and scaling of a Product Catalog Service, Exact Product Matching Service, and Product Search Service.

Bring a strong command of Golang, Python, Vector Databases, and embedding technologies.

Design and build complex systems, architecture, and solutions.

Provide inputs on engineering and operational excellence.

Identify and evaluate new technologies and tools for the engineering team.

Demonstrate ability to solve complex technical challenges and provide innovative solutions.

Create and maintain technical documentation.

Design, develop, and deploy software solutions.

Take ownership of complex issues and act as a technical leader in crisis situations.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

Distributed SystemsSoftware DevelopmentArchitectureCoding StandardsCompliance RequirementsProblem-SolvingTeamworkCommunicationData StorageData ProcessingApache SparkApache FlinkApache BeamHadoop MapReduceApache KafkaApache PulsarAWSAzureGoogle Cloud PlatformAmazon EMRAzure HDInsightGoogle Cloud DataprocDockerKubernetesData ModelingETLOptimization

Required

More than 7 years demonstrating a deep understanding of distributed systems and software development principles, architecture, and best practices.

Degree: A bachelor's or master's degree in Computer Science, Software Engineering, or a related field is preferred, although relevant work experience can sometimes compensate for formal education.

Design, develop and deploy software solutions that meet the needs of the business.

Ensure that the engineering team adheres to coding standards, best practices, and compliance requirements.

Preferred

Data Storage: Expertise in working with various data storage technologies, including relational databases, NoSQL databases (like Hadoop HDFS, Apache Cassandra), and columnar databases.

Data Processing: Strong understanding of data processing frameworks like Apache Spark, Apache Flink, Apache Beam, or Hadoop MapReduce. Experience in designing and optimizing data processing pipelines for performance and scalability is important.

Streaming Data: Knowledge of stream processing frameworks like Apache Kafka or Apache Pulsar is valuable for handling real-time data streams.

Cloud Platforms: Experience with cloud platforms like AWS, Azure, or Google Cloud Platform, and their big data services (e.g., Amazon EMR, Azure HDInsight, Google Cloud Dataproc).

Containerization and Orchestration: Familiarity with containerization (Docker) and orchestration tools (Kubernetes) for deploying and managing big data applications.

Data Modeling and ETL: Understanding of data modeling concepts and experience with Extract, Transform, Load (ETL) processes for transforming and moving data between systems.

Optimization: Proficiency in optimizing big data applications for performance, throughput, and resource utilization.