Job Description
About The Role
We are looking for an experienced Data Engineer to design, build, and maintain scalable data pipelines and warehousing solutions. You will work closely with analytics, data science, and business teams to deliver reliable, high-quality data infrastructure.
Key Responsibilities
Design, develop, and maintain ETL/ELT pipelines to ingest, transform, and load data from diverse sources into the data warehouse
Build and optimize data models in Snowflake using dimensional modeling (star/snowflake schemas) and data vault techniques
Develop and maintain dbt projects including models, tests, macros, and documentation
Monitor pipeline health, troubleshoot failures, and implement alerting and data quality checks
Collaborate with stakeholders to understand data requirements and translate them into technical solutions
Optimize query performance, warehouse sizing, and cost management in Snowflake
Implement CI/CD practices for data pipeline deployments
Ensure data governance, security, and compliance standards are met
Mentor junior engineers and contribute to engineering best practices
Required Qualifications
5+ years of experience in data engineering or a related role
Strong proficiency in SQL and data modeling (dimensional modeling, normalization)
Hands-on experience with Snowflake (architecture, performance tuning, resource monitors, data sharing, streams/tasks)
Production experience with dbt (Core or Cloud) — building modular models, writing tests, managing incremental materializations, and using packages
Proven track record designing and operating ETL/ELT pipelines at scale using tools such as Airflow, Fivetran, Matillion, or equivalent
Experience with data warehouse design principles (Kimball, Inmon, or Data Vault)
Proficiency in Python for data processing and automation
Familiarity with version control (Git) and CI/CD workflows for data projects
