Back
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Strong Tier-1 brand, mid-level generalist data role, metro location, and common skillset increase applicant competition.
Core ETL and PySpark skills are transferable, though banking compliance raises moderate domain sensitivity.
Explicit 4+ years requirement plus mandatory PySpark, Oracle and ETL skills make shortlisting fairly strict.
Lead moderately complex data engineering initiatives related to enterprise-scale data processing frameworks and strategy deliverables.
Build and maintain optimized, highly available ETL data pipelines using PySpark and SQL to enable analytics and reporting.
Oversee data integration tasks including data modeling, maintaining data warehouse and analytics environments, and script development for integration and analysis.
4+ years of data engineering experience including ETL development with PySpark.
3+ years of Oracle database experience.
Proficiency in SQL on platforms such as Oracle, SQL Server, and/or Teradata.
Work Experience Required: 4+ years in Data Engineering explicitly mentioned.
Experienced in designing and optimizing complex SQL queries and troubleshooting ETL and production issues.
Familiar with multiple data ingestion patterns including NDM files, APIs, and direct database connections and working knowledge of Linux environment.
Ability to translate business requirements into technical specifications and operate within Agile Scrum teams using tools like Jira, GitHub, and CI/CD practices.