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Job Description
Structured overview of role & requirementsAbout This Role
Design, build, and optimize scalable batch or near-real-time data pipelines and analytics-ready data models using Snowflake, dbt, Astronomer/Airflow, and Python.
Develop, orchestrate, monitor, and troubleshoot workflows including ELT transformations, data quality checks, and performance tuning to enable reliable business reporting and analytics.
Collaborate cross-functionally to deliver governed, secure, high-performing data solutions adhering to best practices in modular code, version control, CI/CD, testing, and documentation.
Minimum Requirements
Strong hands-on experience with Snowflake for data modeling, query optimization, warehouse management, and secure access.
Proficiency in Python and SQL for ingestion, transformation, automation, validation, and troubleshooting.
Experience with dbt for modular data transformations and Astronomer/Airflow for DAG development, scheduling, monitoring, retries and alerts.
Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
Experienced data engineer with deep expertise in cloud data platforms, especially Snowflake and modern ELT toolchains like dbt.
Skilled in workflow orchestration and production support with Astronomer/Airflow to ensure operational reliability of data pipelines.
Strong operational rigor in implementing engineering best practices including governance, observability, security, and collaboration with cross-functional teams.