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Mid-level generalist data engineer role in metro with common GCP/BigQuery skills increases applicant competition.
GCP-specific data engineering skills transfer across industries, though cloud-platform expertise increases domain sensitivity moderately.
Explicit 6+ years requirement plus mandatory GCP, BigQuery, and PySpark expertise enforces strict filters.
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Design, build, and scale end-to-end data platforms and pipelines on Google Cloud Platform (GCP) using BigQuery and related tools.
Own full development lifecycle from requirements gathering through production deployment and optimization for scalable data workflows.
Develop, optimize, and operationalize data models, pipelines, and analytical datasets to support reporting and data-driven decision-making across the organization.
6+ years of experience in data engineering or related field.
Graduate degree in Computer Science, Data Science, or related field.
Strong programming skills with Python (including PySpark, Pandas) and SQL.
Deep expertise in GCP services, architecture, and scalable data platform design including experience with BigQuery.
Proven track record in building large-scale data pipelines and distributed systems on GCP.
Experience working across the full data engineering development lifecycle from design to deployment and optimization.
Ability to collaborate effectively with cross-functional teams including business, risk, operations, and technology stakeholders.