Back
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Mid-level generalist data engineering role in metro with common skillset increases applicant competition.
Financial-services focus adds domain bias, but core data engineering skills remain reasonably transferable.
Explicit years plus mandatory modern data stack skills (Azure, Snowflake, dbt, PySpark) make filters stringent.
Build and maintain scalable ELT data pipelines and enterprise data warehousing for financial datasets using Azure, Snowflake, dbt, Fivetran, and ADF.
Contribute to data modelling and SQL transformations in Snowflake and dbt, ensuring data workflow reliability and performance monitoring.
Support exploration and integration of Generative AI tools to enhance financial data processing and workflow automation.
1-4 years of experience in Data Engineering with hands-on skills in Azure, Snowflake, dbt, Databricks, Gen AI, SQL, and PySpark.
Experience with ELT pipelines, data warehousing, and data visualization tools like Power BI and Power Platform.
Location requirement: Chennai, Tamil Nadu, India.
Work Experience Required: 3-4 Years explicitly mentioned in the JD.
Experience working in financial data environments, preferably Investment and Wealth Management domain.
Comfortable with modern data engineering stacks including cloud platforms and data transformation frameworks.
Willingness to learn and support advanced AI integrations in data engineering workflows under senior mentorship.