Senior Data Engineer

Key Responsibilities

Data Pipeline Development:

• Design, develop, and maintain scalable and high-performance batch and streaming data pipelines.
• Build and optimize ETL/ELT workflows using tools such as dbt, Airflow, and Python/Scala/Java.

Data Modeling:

• Model, implement, and manage dimensional and relational data models in Snowflake.
• Ensure adherence to architectural standards when working with cloud data warehouses.

Code Quality and Testing:

• Write clean, maintainable, and well-tested code for data processing and transformation.

Collaboration with Engineering Teams:

• Collaborate with DevOps and Platform Engineering teams to ensure data pipelines are reliable, performant, and monitored.

Code Reviews and Best Practices:

• Participate in code reviews, ensuring the team follows best engineering practices.

Troubleshooting and Optimization:

• Diagnose and resolve data pipeline issues related to performance, reliability, and data quality.

Required Skills:

• 10+ years of hands-on experience in data engineering.
• Strong programming skills in Python, Scala, or Java.
• Expert-level SQL proficiency with a focus on query optimization.
• Proven and deep experience with Snowflake or similar 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 (e.g., Docker, Kubernetes) and CI/CD workflows.