Backend Data engineer

•       5+ years of software engineering experience with a focus on backend systems and/or data platforms

•       Strong PostgreSQL skills — schema design, normalization, indexing strategies, query optimization, and understanding of execution plans (EXPLAIN ANALYZE)

•       Hands-on experience with database migration tools — Django Migrations, Alembic, Flyway, Liquibase, or similar. Must understand forward and rollback migrations, dependency ordering, and safe deployment of schema changes in production

•       Proficiency in Python for backend development — Django or FastAPI experience strongly preferred

•       Hands-on experience with at least one major cloud platform (AWS, GCP, or Azure) — managed databases, compute, or storage services in a production environment. Azure experience is a plus given the team’s direction, but is not mandatory

•       Experience reading and interpreting product requirement documents (PRDs) and translating them into data models and technical implementations

•       Solid understanding of relational database fundamentals — ERD design, normalization (3NF and beyond), referential integrity, and transaction management

•       Familiarity with Git-based workflows, CI/CD pipelines, containerization (Docker) and basic orchestration (Kubernetes / AKS), and agile development practices

•       Strong communication skills — ability to discuss schema trade-offs, propose alternatives, and document decisions clearly

•       Conceptual familiarity with data engineering fundamentals — understanding of ETL/ELT concepts, batch vs. streaming data flows, and data lake/warehouse patterns

Preferred

Data Engineering & Cloud (Upcoming Team Focus)

•       Experience with Azure cloud services — Data Factory, Data Lake Gen2, Synapse Analytics, Event Hub, Azure SQL, Cosmos DB

•       Hands-on ETL/ELT pipeline development — ingestion, transformation, orchestration using tools like Apache Airflow or Azure Data Factory

•       Understanding of data lake architectures and medallion (bronze/silver/gold) layering patterns

•       Experience with Azure Data Explorer (ADX) and Kusto Query Language (KQL)

•       Familiarity with Snowflake, BigQuery, or other cloud data warehousing platforms

Backend & Systems

•       Experience with NoSQL databases (MongoDB, Cosmos DB) — data modeling, aggregation pipelines

•       Understanding of event-driven architecture, messaging systems (Kafka, Event Hub), and pub/sub patterns

•       Understanding of distributed systems concepts — partitioning, replication, consistency trade-offs

•       Experience with streaming frameworks (Spark Structured Streaming, Azure Stream Analytics)

Domain & Other

•       Prior experience in retail, supply chain, or large-scale e-commerce systems

•       Familiarity with dbt or similar ELT transformation tools

•       Experience with IoT data pipelines and real-time telemetry processing

We are looking for a Backend & Data Engineer to join a cross-functional engineering team building and scaling a cloud-based platform in the retail and supply chain domain. The role is centered on backend and database engineering — designing PostgreSQL schemas, writing and maintaining migration scripts, reviewing PRDs to recommend schema and performance optimizations, and contributing to a Django-based application. As the team expands into data platform modernization on Azure, a working knowledge of data engineering concepts will be increasingly valuable.

This is a hands-on engineering role. You will own schema design decisions, write production-grade migration scripts, debug query performance issues, and work closely with product and platform teams to deliver features end-to-end.

What You Will Do

•       Design, review, and optimize PostgreSQL schemas for new application features — define tables, indexes, constraints, and relationships based on PRDs and technical requirements

•       Write and maintain database migration scripts using Django Migrations (or equivalent ORM-based migration tools), ensuring migrations are reversible, tested, and production-safe

•       Review product requirement documents (PRDs), identify data modeling implications, and proactively suggest schema or query optimizations before development begins

•       Diagnose and resolve database performance issues — slow queries, missing indexes, lock contention, connection pooling, and query plan analysis

•       Contribute to the Django application codebase — defining and updating models, writing and reviewing migration scripts, and ensuring schema changes align with application requirements

•       Collaborate with data scientists, product managers, and frontend engineers to translate business needs into robust data models

•       Participate in code reviews, system design discussions, and technical documentation

•       Support the team's Azure migration efforts as they ramp up — contributing to data pipeline design, ETL development, and cloud infrastructure decisions