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 Do
- Design 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 BigQuery.
- 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 BigQuery.
- 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.
