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Mid-level metro Data Engineer with common Snowflake/DBT skills and a recognized bank brand increases competition.
Transferable data engineering skills, but banking and regulatory familiarity moderately increases background sensitivity.
Multiple mandatory technical skills (Snowflake, DBT, Airflow, Python, SQL) plus 5+ years experience increases strictness.
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Design and build enterprise-level data pipelines and develop/maintain large-scale data platforms including data warehouses and data lakes.
Create data ingestion pipelines from varied sources (files, databases, APIs, SharePoint) using tools like Python, SQL, and orchestration with Airflow or scheduling tools.
Perform performance tuning for complex data pipelines and SQL queries, handle impact analysis, and provide technical support for production incidents; collaborate with global teams primarily in the US.
5+ years of experience in building data pipelines on Data Warehouse and Data Lake platforms.
Strong expertise in Snowflake data platform and AWS cloud services (S3, Lambda, Glue, Step Function, CloudWatch).
Proficiency with ELT tools such as DBT, and scripting languages including Python and Unix shell.
Work Experience Required: 5+ years in relevant data engineering roles; Location: Bangalore (Hybrid).
Experienced in enterprise data platform design including integration, security, privacy, and governance aspects in financial industry context or similar regulated environments.
Strong technical skills across Snowflake, AWS cloud services, ELT tools (DBT), SQL optimization, and data modeling (Logical and Physical; Dimensional or Relational).
Comfortable working in Agile teams coordinating with product owners, global cross-functional stakeholders, and managing production support with impact analysis capabilities.