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Mid-level Bangalore data engineering role with common title and broad GCP skillset increases competition.
Data engineering skills transfer across industries, though GCP and medallion architecture add moderate specificity.
Explicit 3+ years plus mandatory GCP, BigQuery, Airflow, SQL and Python requirements make screening strict.
Build and maintain scalable data engineering pipelines and integrations on Google Cloud Platform focusing on the bronze layer of medallion architecture.
Ingest data from internal and external sources into the enterprise data lake and modernize legacy data systems and workflows.
Collaborate with business stakeholders and technical teams to gather requirements, support testing, and design solutions that improve data reliability, usability, and scalability.
Bachelor’s degree in Data Engineering, Data Science, Computer Science, IT, or a related field.
3+ years of experience in data engineering, cloud data platforms, or related roles.
Hands-on experience with Google Cloud Platform data tools such as BigQuery, Cloud Composer (Airflow), and Cloud Data Fusion.
Strong SQL skills and experience building ETL/ELT pipelines for structured and semi-structured data.
Experienced in legacy system analysis and migration to cloud-based data architectures, particularly medallion architecture bronze-layer ingestion.
Comfortable working independently with a hands-on engineering mindset from analysis through delivery in cross-functional/global teams.
Able to communicate effectively with both technical teams and business stakeholders, translating business needs into technical solutions.