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Common mid-level data role in Bengaluru with 3-6yr range and broad toolset increases competition.
Tools are transferable across industries, but insurance domain knowledge moderately increases hiring preference.
Explicit 4+ years, 1+ year GCP, and mandatory BigQuery/DBT/Airflow make filters strict.
Design, develop, and operationalize scalable data pipelines with automated quality checks using GCP services and related technologies.
Lead end-to-end pipeline development from data ingestion to consumption, optimizing ETL processes and ensuring high performance, availability, and scalability.
Maintain and optimize data models and schemas for analytics, implement monitoring, troubleshooting, and uphold rigorous data quality standards.
4+ years in Data/ETL Engineering with at least 1 year of Google Cloud Platform (GCP) development experience.
Proven experience building and maintaining scalable Cloud Data Warehouses, preferably with Google BigQuery.
Proficiency in SQL, Python, DBT, Apache Airflow, and ETL tools like Talend or Fivetran; familiarity with data modeling concepts like star and snowflake schemas.
Bachelor’s degree in Computer Science, MIS, CIS, or equivalent; strong skills in Git for version control.
Strong expertise in GCP data services (DataProc, Dataflow, BigQuery) and cloud-native data engineering best practices.
Experienced in creating automated data quality checks and reusable components in ETL pipelines for efficient, scalable operations.
Capable of designing data models and handling complex data integration using SQL, Python, and modern orchestration tools in a collaborative environment.