Software Development Engineer II (Data Engineering)

We’re looking for a Software Development Engineer II (Data Engineering) to join our growing Data Engineering team. In this role, you will design, build, and operate scalable data platforms, pipelines, and services that power analytics, engineering, and Data Science across Quince.

You will work closely with engineering and business stakeholders to translate complex data requirements into reliable and scalable technical solutions. You will take ownership of data engineering modules end-to-end, contribute to system design and architecture, and continuously improve the performance, reliability, and scalability of our data infrastructure.

This role is ideal for an engineer who enjoys solving complex data problems, working with large-scale distributed systems, and spending the majority of their time building and improving production systems.

Own low-level system design and implementation for data engineering components.

Design highly available and fault-tolerant services for data ingestion, processing, and extraction.

Optimize data systems for performance, scalability, reliability, and read/write latency.

Apply distributed computing principles to build systems that can efficiently process large and complex datasets.

Identify bottlenecks and continuously improve the efficiency of data pipelines and services.

Work with large-scale data processing technologies such as Hadoop, Spark, Hive, and Presto.

Evaluate, research, and integrate modern data engineering frameworks and technologies as the platform evolves.

Build and maintain streaming and event-driven data pipelines using technologies such as Kafka, Kinesis, or RabbitMQ.

Design solutions for processing and integrating data from multiple sources and formats.

Partner closely with engineering, analytics, Data Science, and business stakeholders to understand requirements and translate them into scalable technical solutions.

Work effectively through ambiguity by identifying problems, evaluating trade-offs, and driving solutions to completion.

Communicate technical decisions and system designs clearly across teams.

Contribute to code reviews, technical discussions, and engineering standards.

Spend the majority of your time on hands-on development, technical problem-solving, and research.

Monitor and maintain production data pipelines, services, and workflows.

Debug and resolve data quality, performance, reliability, and production issues.

Establish appropriate monitoring and operational practices for critical data systems.

Continuously improve the reliability, scalability, and operational efficiency of data infrastructure.

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 programming language such as Python, Java, or Scala.

Experience building highly available and fault-tolerant services, preferably for data ingestion or data extraction.

Strong understanding of data warehousing fundamentals and data modelling concepts.

Strong SQL skills, including experience with technologies such as Spark SQL, HiveQL, T-SQL, or PL/SQL.

Experience integrating, transforming, and processing data from multiple sources.

Good understanding of distributed computing and large-scale data processing principles.

Strong analytical and problem-solving skills with the ability to work with large and complex datasets.

Experience working with production data systems and troubleshooting performance and reliability issues.

Ability to work independently while collaborating effectively with cross-functional teams.

Preferred:

Experience working with cloud-native data services, particularly AWS.

Experience with MPP data warehouses such as Snowflake or Redshift.

Strong proficiency with Apache Spark and Apache Kafka.

Experience with NoSQL databases such as Redis, DynamoDB, or Memcached.

Experience designing and operating large-scale, highly available data platforms.

Experience with data quality, monitoring, observability, and production data operations.

Familiarity with containerization, CI/CD, and modern cloud-native engineering practices.

Experience working in a high-growth technology, e-commerce, or data-intensive environment.

WHY QUINCE?

Joining Quince means being part of a mission-driven team reshaping retail. You will work alongside talented colleagues, tackle meaningful challenges, and contribute to building a more sustainable, accessible future for customers and partners alike.

EQUAL OPPORTUNITY & HIRING INTEGRITY

Quince provides equal employment opportunities to all employees and applications for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran or military status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws.

Quince is committed to providing reasonable accommodations to qualified individuals with disabilities. If you need a reasonable accommodation to complete your application or to perform the essential functions of a role at Quince, please let us know by completing this accommodation form. We review all requests individually and will work with you to determine appropriate accommodations on a case-by-case basis.

Employment is contingent upon successful completion of a background check. Quince will conduct background checks in compliance with applicable federal, state, and local laws.

Security Advisory: Beware of Frauds

At Quince, we're dedicated to recruiting top talent who share our drive for innovation. To safeguard candidates, Quince emphasizes legitimate recruitment practices. Initial communication is primarily via official Quince email addresses and LinkedIn; beware of deviations. Personal data and sensitive information will not be solicited during the application phase. Interviews are conducted via phone, in person, or through the approved platforms Google Meets or Zoom—never via messaging apps or other calling services. Offers are merit-based, communicated verbally, and followed up in writing. If personal information is requested to initiate the hiring process, rest assured it will be through secure and protected means.