Job
Description
At Aramya, we’re redefining fashion for India’s underserved Gen X/Y women, offering size-inclusive, comfortable, and stylish ethnic wear at affordable prices. Launched in 2024, we’ve already achieved ₹40 Cr in revenue in our first year, driven by a unique blend of data-driven design, in-house manufacturing, and a proprietary supply chain. Today, with an ARR of ₹100 Cr, we’re scaling rapidly with ambitious growth plans for the future. Our vision is bold to build the most loved fashion and lifestyle brands across the world while empowering individuals to express themselves effortlessly. Backed by marquee investors like Accel and Z47, we’re on a mission to make high-quality ethnic wear accessible to every woman. We’ve built a community of loyal customers who love our weekly design launches, impeccable quality, and value-for-money offerings. With a fast-moving team driven by creativity, technology, and customer obsession, Aramya is more than a fashion brand—it’s a movement to celebrate every woman’s unique journey. We’re looking for a passionate Data Engineer with a strong foundation. The ideal candidate should have a solid understanding of D2C or e-commerce platforms and be able to work across the stack to build high-performing, user-centric digital experiences. Key Responsibilities Design, build, and maintain scalable ETL/ELT pipelines using tools like Apache Airflow, Databricks , and Spark . Own and manage data lakes/warehouses on AWS Redshift (or Snowflake/BigQuery). Optimize SQL queries and data models for analytics, performance, and reliability. Develop and maintain backend APIs using Python (FastAPI/Django/Flask) or Node.js . Integrate external data sources (APIs, SFTP, third-party connectors) and ensure data quality & validation. Implement monitoring, logging, and alerting for data pipeline health. Collaborate with stakeholders to gather requirements and define data contracts. Maintain infrastructure-as-code (Terraform/CDK) for data workflows and services. Must-Have Skills Strong in SQL and data modeling (OLTP and OLAP). Solid programming experience in Python , preferably for both ETL and backend. Hands-on experience with Databricks , Redshift , or Spark . Experience with building and managing ETL pipelines using tools like Airflow , dbt , or similar. Deep understanding of REST APIs , microservices architecture, and backend design patterns. Familiarity with Docker , Git, CI/CD pipelines. Good grasp of cloud platforms (preferably AWS ) and services like S3, Lambda, ECS/Fargate, CloudWatch. Nice-to-Have Skills Exposure to streaming platforms like Kafka, Kinesis, or Flink. Experience with Snowflake , BigQuery , or Delta Lake . Proficient in data governance , security best practices, and PII handling. Familiarity with GraphQL , gRPC , or event-driven systems. Knowledge of data observability tools (Monte Carlo, Great Expectations, Datafold). Experience working in a D2C/eCommerce or analytics-heavy product environment. Show more Show less
