Backend / Data Software Engineer

Role Description

We are seeking a versatile Backend Software Engineer with a strong interest and capability in Data Engineering to join our team. In this role, you won't be boxed into a single domain. Instead, you will act as a bridge between core backend application development and robust data infrastructure.

You are a great fit if you consider yourself a software engineer first, but you possess a deep appreciation for data pipelines, scalability, and distributed systems. You will design and build robust backend services while simultaneously shaping how our data is ingested, processed, and stored.

Key Responsibilities

• Backend Development: Design, build, and maintain scalable, high-performance backend services and APIs using Python.
• Data Pipeline Engineering: Architect and optimize reliable ETL/ELT pipelines to process large volumes of data using PySpark.
• System Architecture: Containerize applications and data jobs for seamless deployment across environments.
• Data Modeling & Storage: Design efficient relational database schemas and optimize complex SQL queries for both transactional and analytical workloads.
• Collaboration: Work closely with product, analytics, and data science teams to understand data requirements and deliver production-ready software solutions.
• Python: Strong proficiency in writing clean, testable, and efficient production code (e.g., using frameworks like FastAPI, Flask, or standard library concurrency).
• SQL: Advanced knowledge of SQL (joins, window functions, query optimization) and experience working with relational databases (e.g., PostgreSQL, MySQL).
• PySpark & Big Data: Hands-on experience using PySpark for distributed data processing and large-scale data manipulation.
• Docker: Experience containerizing applications and managing local or production deployments using Docker/Docker Compose.
• Engineering Mindset: Strong grasp of software engineering best practices, including git version control, CI/CD, code reviews, and writing unit/integration tests.

Qualifications

• Experience with Apache Iceberg for managing large-scale analytic datasets and table formats.
• Familiarity with cloud storage solutions and optimization techniques, specifically AWS S3 / S3 Tables.
• Familiarity with data ingestion and orchestration tools (e.g., AWS Glue, AWS Step Functions).