Data Engineer About the Role As a Data Engineer at Aspire, you will design, build, and maintain scalable data pipelines to support production data workflows. You will implement end-to-end ETL/ELT pipelines, optimize data processing, and integrate pipelines with internal systems and cloud-based data warehouses. You will collaborate with cross-functional teams to ensure reliable, high-performance data solutions. What You'll DoDesign and implement full ETL/ELT pipelines from data ingestion to transformation and delivery. Develop scalable and maintainable data workflows using Python. Integrate data pipelines with multiple internal systems and modules. Work with cloud-based data warehouses such as Snowflake or Big Query. Optimize SQL queries and ensure high-performance data processing. Apply best practices in data engineering and data warehousing architecture. Troubleshoot and resolve production data issues. Contribute to CI/CD and deployment processes for data pipelines. What You'll Need Strong experience with Python (most critical requirement). Very strong SQL skills (query optimization, joins, aggregations, performance tuning). Experience with cloud data warehouses such as Snowflake or Big Query. Solid understanding of data engineering principles, ETL/ELT architecture, and data warehouse concepts (fact/dimension modeling, partitioning, indexing). Around 5 years of experience in data engineering or related roles (flexible for strong candidates). Proven experience building production-grade data pipelines. Familiarity with Kafka, CDC (Change Data Capture), monitoring tools, Docker, Kubernetes, or CI/CD tooling is a plus. Experience with Java is a bonus. Strong problem-solving and debugging skills for production data workflows. Ability to analyze and improve AI-generated code snippets is a plus. Awareness or knowledge of IT security best practices as defined by ISO/SOC or similar.