RESPONSIBILITIES:
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.
Solid programming skills in Python, Scala, or Java.
Expert-level SQL proficiency with a solid 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.