- Design, develop, and maintain large-scale batch and streaming data pipelines.
- Build and optimize production-grade ETL/ELT workflows using tools such as dbt, Airflow, and Python/Scala/Java.
- Model, implement, and manage dimensional and relational data models in Snowflake following architectural standards.
- Write clean, maintainable, and well-tested code for data processing and transformation.
- Collaborate with DevOps and Platform Engineering teams to ensure pipelines are reliable, performant, and monitored.
- Participate in code reviews and promote best engineering practices.
- Diagnose and resolve data pipeline issues related to performance, reliability, and quality.
Required Skills:
Must-Have:
- 10+ years of hands-on experience in data engineering.
- Strong programming skills in Python, Scala, or Java.
- Expert-level SQL proficiency with a strong focus on query optimization.
- Proven and deep experience with Snowflake or similar up-to-date cloud data warehouses.
- Solid track record of building and orchestrating data pipelines using Airflow, dbt, or equivalent tools.
- Hands-on experience with Apache Spark or other big data technologies.
- Experience with containerization (Docker, Kubernetes) and CI/CD workflows.