Engineer Lead, Software (Snowflate, Python, DBT)
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Protocol Intelligence
Data-driven signals on your job's competitivenessTier-1 brand, popular Data Engineer title, metro hiring, and broad skills increase applicant competition.
Core data engineering skills are transferable across industries, though fintech governance adds domain specificity.
Mandatory Snowflake, dbt, Airflow, Python experience and senior 'Lead' title imply strict technical filters.
Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, and maintain scalable batch and near-real-time data pipelines using Snowflake, Python, dbt, and Astronomer/Airflow.
Build and optimize data models, ELT workflows, and automated data quality checks to support analytics and reporting.
Ensure data quality, governance, security, and operational reliability across enterprise data pipelines.
Minimum Requirements
Strong hands-on experience in data engineering, ETL/ELT development, data warehousing, and pipeline orchestration.
Proficiency in Python and SQL for data ingestion, transformation, automation, validation, and troubleshooting.
Experience with Snowflake data modeling, query optimization, warehouse management, and security.
Experience with dbt for modular data transformations and Astronomer/Airflow for workflow orchestration.
Ideal Candidate Profile
Experienced data engineer skilled in modern cloud data platforms and orchestration tools like Snowflake, dbt, and Airflow.
Operationally focused with strong discipline in engineering best practices including testing, version control, CI/CD readiness, and peer reviews.
Able to collaborate across analysts, product, business, architecture, and platform teams to deliver trusted, governed, high-performing data solutions.