Design and build scalable backend microservices, data pipelines, and integration services with minimal oversight, ensuring high code quality, reliability, and performance
Develop and maintain master data management solutions that ensure consistency, accuracy, and governance of core business entities across the enterprise
Write modular, testable, resilient, production-grade code with strong attention to edge cases, idempotency, and data integrity
Design and implement data models, schemas, and APIs that support domain-driven design principles and composable, event-driven architectures
Leverage AI/ML tools (Claude Code, GitHub Copilot, etc.) to enhance developer productivity, automate data quality checks, and integrate intelligent capabilities into data workflows
Implement and optimize RESTful/GraphQL APIs and event-driven integrations (Kafka, message queues) with internal and third-party systems
Effectively debug and resolve production issues across distributed systems. Identify and communicate potential risks. Participate in Root Cause Analysis (RCA) sessions
Collaborate effectively with architects, data engineers, product managers, and domain stakeholders. Clearly communicate technical information to both technical and non-technical audiences

Requirements

Bachelor’s degree in Computer Science, Data Science, or equivalent practical experience
3 – 5 years of experience in software development with a strong focus on backend systems, data engineering, or data platform development
Mastery of at least one modern programming language (e.g. Go, Python, Java) with deep understanding of algorithms, data structures, concurrency, and optimization
Expertise in building RESTful/GraphQL APIs, microservices architecture, and event-driven systems (Kafka, SNS/SQS)
Strong understanding of data modeling (dimensional, relational, graph), schema evolution, and data governance practices including master data management concepts: entity resolution, data stewardship, golden record creation, and cross-system data synchronization
Strong knowledge of SQL (PostgreSQL, MySQL) and NoSQL databases (Cassandra, MongoDB, Redis), with experience in data warehousing platforms (Snowflake, Redshift, BigQuery) and data lake architectures
Experience with AWS (or other cloud providers) utilizing services such as EC2, S3, Lambda, Step Functions, Glue, EMR, and ECS/EKS. Understanding of infrastructure-as-code (Terraform, CloudFormation) and CI/CD pipelines
Proficiency using AI-powered development tools (Claude Code, GitHub Copilot) for code generation, refactoring, and documentation. Understanding of prompt engineering and LLM integration patterns for building AI-augmented data workflows
Experience in retail, ecommerce, or consumer goods industries preferred. Strong problem-solving and debugging skills across distributed backend systems, data pipelines, and integration layers.

Benefits

Health insurance
401(k) matching
Flexible time off
Paid maternity/paternity leave
Infertility treatment
Wellness programs with fitness and weight management partners

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

backend developmentdata engineeringmicroservices architectureRESTful APIsGraphQL APIsdata modelingSQLNoSQLdata warehousingcloud computing

Soft Skills

problem-solvingdebuggingcollaborationcommunicationattention to detailrisk identificationtechnical communication

Certifications

Bachelor’s degree in Computer ScienceBachelor’s degree in Data Science