1 day ago
Bengaluru, IndiaMid Level
Responsibilities
- Design, build, and maintain scalable data pipelines, platforms, tools, and services.
- Develop cloud-based data engineering solutions for analytics, engineering, and Data Science use cases.
- Build ingestion, transformation, processing, extraction, streaming, and event-driven workflows across multiple sources and formats.
- Own data engineering modules from system design and implementation through production operations.
- Design highly available and fault-tolerant services and optimize data systems for performance, scalability, reliability, and latency.
- Apply distributed computing principles to large-scale data processing and resolve data quality, performance, reliability, and production issues.
- Collaborate with engineering, analytics, Data Science, and business stakeholders; contribute to code reviews, technical discussions, and engineering standards.
- Establish monitoring and operational practices and continuously improve data infrastructure reliability and efficiency.
Requirements
- 4+ years of experience in Data Engineering, Software Engineering, or a related technical field.
- Strong experience with big data technologies such as Hadoop, Spark, Hive, or Presto.
- Experience with streaming and messaging platforms such as Kafka, Kinesis, or RabbitMQ.
- Strong proficiency in at least one of Python, Java, or Scala.
- Experience building highly available and fault-tolerant services, preferably for data ingestion or extraction.
- Strong understanding of data warehousing fundamentals, data modeling, distributed computing, and large-scale data processing.
- Strong SQL skills, including Spark SQL, HiveQL, T-SQL, or PL/SQL.
- Experience integrating, transforming, and processing data from multiple sources.
- Experience operating production data systems and troubleshooting performance and reliability issues.
- Ability to work independently, solve complex problems, and collaborate effectively with cross-functional teams.
- Preferred: experience with AWS, Snowflake or Redshift, Redis, DynamoDB, Memcached, large-scale data platforms, data quality and observability, and modern cloud-native engineering practices.
- Preferred: experience in a high-growth technology, e-commerce, or data-intensive environment.
Benefits
- Join a mission-driven team reshaping retail and contribute to a more sustainable and accessible future.
- Employment is contingent upon successful completion of a background check.
- Reasonable accommodations are available for qualified individuals with disabilities.
Tech Stack
Amazon DynamoDBAmazon RedshiftApache HadoopApache HiveApache KafkaApache SparkAWSJavaPrestoPythonRabbitMQRedisScalaSnowflakeSQL
Categories
Data Engineering
About Quince
Quince is a direct-to-consumer ecommerce retailer that sells apparel, accessories, and home goods by connecting shoppers directly with manufacturing partners. Its manufacturer-to-consumer model uses demand-driven production and price transparency (including cost breakdowns) to reduce middlemen and inventory waste. Founded in 2018 and headquartered in San Francisco, the privately held company offers curated essentials across categories such as cashmere, linen, jewelry, and furniture through its online storefront.