• 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