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Metro location, mid-level generalist Data Engineer title, broad skills and GCP focus increase candidate competition.
Technical data engineering skills are transferable across industries, though GCP specialization and domain experience moderately increase fit sensitivity.
Mandatory six years plus required GCP/BigQuery/Spark/Python skills enforce strict shortlisting filters.
Architect, develop, and maintain scalable data pipelines on Google Cloud Platform (GCP) for enterprise analytics and reporting.
Collaborate with business, analytics, and data science teams to implement optimized data workflows ensuring data quality, security, and governance.
Optimize ingestion, transformation, and processing workflows with focus on performance, cost efficiency, and operational reliability.
Minimum 6 years of data engineering experience with significant focus on GCP and Big Data ecosystems.
Strong hands-on expertise with GCP services including BigQuery, Dataflow, Cloud Storage, and Pub/Sub.
Proficiency in Apache Spark, Python programming for data scripting and automation, and experience building ETL/ELT pipelines.
Bachelor’s or Master’s degree in Computer Science, Data Science, IT, or related field.
Experienced in operating within agile, cross-functional teams supporting large-scale or enterprise data platforms.
Demonstrates expertise in distributed data processing, infrastructure automation, and enforcing data security and governance.
Has worked in domains such as finance, healthcare, retail, or technology and can lead data engineering best practices and mentor peers.