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Mid-level popular Data Engineer title with metro location and broad GCP/Spark requirements increases competition.
Core data engineering skills transfer across industries, though GCP and domain knowledge add moderate specificity.
Explicit mandatory 6+ years and specific GCP/BigQuery/Spark pipeline experience enforces strict shortlisting.
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Architect, develop, and maintain scalable data pipelines on GCP supporting enterprise analytics and reporting.
Collaborate with cross-functional teams to translate business requirements into optimized data workflows with high performance and security.
Implement and enforce data quality, security, and governance standards across platforms and troubleshoot pipeline issues for operational reliability.
Minimum 6 years of data engineering experience with a significant focus on GCP and Big Data technologies.
Proficient in GCP services including BigQuery, Dataflow, Cloud Storage, Pub/Sub, and Apache Spark for distributed data processing.
Strong programming skills in Python; experience with ETL/ELT data pipelines and distributed data storage (PostgreSQL, MySQL, MongoDB).
Bachelor's or Master's degree in Computer Science, Data Science, Information Technology, or related field.
Experienced in designing end-to-end scalable and secure data pipelines on GCP within enterprise or large-scale environments.
Capable of collaborating effectively with stakeholders such as data scientists, analytics teams, and business units to align data solutions with organizational goals.
Skilled in applying data governance, security best practices, and infrastructure automation, with familiarity in agile team environments and continuous improvement initiatives.