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Popular Data Engineer role with broad Snowflake/dbt requirements increases competition despite non-Tier1 brand.
Strong financial services lending background and domain-specific ODS experience limits cross-industry transferability.
Multiple mandatory skills (7+ years, Snowflake, dbt, Informatica, Python, financial services) enforce strict shortlisting.
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Assess and improve SQL Server and Snowflake environments by identifying pipeline gaps, data quality issues, and inefficiencies.
Build, maintain, and automate data pipelines and database schema deployments supporting the Operational Data Store (ODS), including batch-to-API migration projects.
Collaborate with data architects and domain teams to ensure data accuracy, lineage, schema standards, and implement automated data quality and testing frameworks.
7+ years of experience in data engineering focusing on pipeline development, CI/CD setup, and database modeling.
Strong proficiency in SQL (SQL Server and Postgres), Python, and Snowflake schema design and performance tuning.
Hands-on experience with DevOps/DataOps pipelines (Git, CI/CD tools), database migration/schema management tools (dbt, Schemachange, Flyway), and ETL/ELT tools (Informatica preferred).
Experience in financial services or lending domain is mandatory.
Experienced in modern data engineering infrastructure with expertise in batch and API data workflows and ODS/dimensional modeling.
Familiarity with generative AI coding assistants to enhance development productivity and testing automation.
Able to work collaboratively with architects and domain teams to standardize data models, enforce naming conventions, and support data governance efforts.