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Strong consultancy brand, common data-engineer title, mid-level experience band, and metro location increase competition.
Medium: core GCP and data skills transferable, but financial-services domain experience and GCP specialization matter.
Explicit 5–8 years plus mandatory GCP, Python, SQL and BigQuery requirements tighten shortlisting.
Develop, test, and maintain data pipelines and ETL/ELT processes using Python, SQL, and Google Cloud Platform services.
Write and optimize complex SQL queries in BigQuery for data transformation, extraction, and analysis.
Troubleshoot data pipeline issues and ensure data accuracy and availability within large-scale data projects on Google Cloud Platform.
Bachelor's degree in Computer Science, IT, Engineering, or related field.
5-8 years of hands-on experience with Python programming for data manipulation.
Proficiency in SQL and experience with Google Cloud Platform, especially BigQuery and Pub/Sub.
Strong understanding of data warehousing concepts and ETL/ELT processes.
Experienced data engineer with 5-8 years focused on Python, SQL, and Google Cloud data services.
Comfortable working in large project teams collaborating with engineers and data analysts.
Familiar with data pipeline troubleshooting, optimization, and data warehouse design within GCP environments.